Predictors of Relationship Satisfactionin Online Romantic RelationshipsTraci L. Anderson & Tara M. Emmers-Sommer

Based on traditional theories of interpersonal relationship development and on the

hyperpersonal communication theory, this study examined predictors of relationship

satisfaction for individuals involved in online romantic relationships. One hundred-

fourteen individuals (N¼114) involved in online romantic relationships, and who had

only engaged in computer-mediated communication (CMC) with their partners, com-

pleted an online questionnaire about their relationships. Intimacy, trust, and communi-

cation satisfaction were found to be the strongest predictors of relationship satisfaction

for individuals involved in online romances. Additionally, perceptions of relationship

variables differed depending on relationship length and time spent communicating.

Implications for interpersonal and hyperpersonal communication theories, and future

investigation of online relationships, are discussed.

Keywords: Computer-Mediated Communication; Relationship; Online; Satisfaction;

Uncertainty; Hypersonal; Interpersonal

More people are becoming involved in computer-mediated romantic relationships.

These individuals inhabit an interesting relational niche because they engage in rela-

tionships that are perceived by some scholars as either nontraditional or understu-

died (Emmers-Sommer, 2005). Given these atypical relational circumstances, such

individuals might also lack information about online romantic relationships and

social support networks from which to gain confirmation about their relationship.

Manuscript accepted for publication with minor revisions in Communication Studies, June 2005. Traci

Anderson (Ph.D., University of Oklahoma) is Assistant Professor at Bryant University. Tara Emmers-Sommer

(Ph.D., Ohio University) is Associate Professor at the University of Nevada-Las Vegas. This manuscript repre-

sents a portion of the first author’s dissertation that was directed by the second author. An earlier version of this

paper was presented at International Network on Personal Relationships conference in 2001. The authors would

like to thank two anonymous reviewers and Jim Query for their helpful comments. Correspondence to: Traci L.

Anderson, Bryant University, 1150 Douglas Pike, Smithfield, RI, 02917, U.S.A. Tel: (401) 232-6582; E-mail:

tanderso@bryant.edu

Communication Studies

Vol. 57, No. 2, June 2006, pp. 153–172

ISSN 1051-0974 (print)/ISSN 1745-1035 (online) # 2006 Central States Communication Association

DOI: 10.1080/10510970600666834

Although there is an abundance of research on romantic relationships in general,

there is still much to be learned about relationships that form in online settings. The-

oretically, current interpersonal theories do not completely account for the develop-

ment of, or what occurs within, online romantic relationships (Merkle & Richardson,

2000). Practically speaking, it is possible that people in online romantic relationships

will experience relationship problems or struggle with the stigma that comes from

having an online romantic relationship (Wildermuth, 2004) as people tend to per-

ceive online relationships negatively (Anderson, 2005), thus, people might seek coun-

seling from a practitioner who, at the present time, would be hard pressed to find any

substantial research on online romantic relationships.

To date, there has been minimal research conducted in the area of computer-

mediated romantic relationships. Much of the existing research has been concerned with

how online relationships are initially established or perceived and managed as ‘‘real’’

relationships (Parks & Floyd, 1996). Such research is indeed valuable, yet we must also

study other aspects of these relationships, such as what contributes to online relation-

ship success. Researchers are beginning to take note of this issue (e.g., Baker, 2002;

Rumbough, 2001); however, few studies of online interpersonal relationship ‘‘success’’

or satisfaction have been published. We seek to establish which predictors of face-to-face

(FTF) relationship satisfaction hold true for online romantic relationships. Indeed, to

further our understanding of what contributes to successful online romantic relation-

ships it would be fruitful to examine what predicts online romantic relationship satis-

faction. Thus, the purpose of this study is to examine the extent to which similarity,

commitment, intimacy, trust, attributional confidence, and communication satisfaction

predicts relational satisfaction in online romantic relationships.

Computer-Mediated Communication and Relating

Initial research on computer-mediated communication (CMC) incorporated such

theories as media richness theory (Draft, Lengel, & Trevino, 1987) and social pres-

ence theory (Short, Williams, & Christie, 1976), currently known as the ‘‘cues filtered

out’’ perspective (Culnan & Markus, 1987). Proponents of the cues filtered out per-

spective advocated that CMC was not conducive for forming close ties online due to

the minimal social context and nonverbal cues inherent to CMC. Some went so far as

to suggest that online relationships, if formed, were ‘‘inauthentic’’ (e.g., Chenault,

1998). However, more recent research indicates that CMC does allow for people to

achieve closeness through communicating online. By extending previous theoretical

work on CMC, such as the social information processing (SIP) model (Walther,

1992) and the social identification=deindividuation (SIDE) model (Spears & Lea,

1994), Walther (1996) proposed a ‘‘hyperpersonal model’’ of CMC. He argued that

online interpersonal communication lends itself to rapidly developing relationships

because CMC is more intimate and moves more quickly than FTF communication.

According to Walther, this closeness develops due to the sender’s ability to carefully

present him- or herself, the afforded ability to edit messages before sending them, the

receiver’s tendency to form positive and ideal partner attributions, and the dyad’s

154 T. L. Anderson & T. M. Emmers-Sommer

level and intensity of self-disclosure. These factors then combine cyclically such that

online communicators reinforce one another’s perceptions of the idealized partner.

Many researchers have conducted studies in which the cues filtered-out model was

shown to be inaccurate for explaining much of what occurs in online interactions.

Walther and Burgoon (1992) found that in the initial stages of online relationship

development, individuals are less open and self-disclose more slowly. However, later

studies (Walther, 1993, 1996) demonstrated that individuals in such relationships

quickly adapt to the lack of bandwidth. Walther (1996) has noted that CMC over-

comes certain limitations of FTF interactions by providing a context in which people

can interact with relative anonymity (or pseudonymity). Once in an online environ-

ment, persons may alter their names, physical presence, or any other personal detail

about which they might feel uncomfortable or self-conscious (Lea & Spears, 1995).

The de-emphasis of physical presence is conducive to genuine, free, and open com-

munication (e.g., Myers, 1987) and subsequently may reduce communication appre-

hension (Sproull & Kiesler, 1991).

The above might help to explain how people form online social and personal rela-

tionships. Parks and Roberts (1998) investigated personal relationships in various types

of multi-user domains (MUDs) and discovered that nearly 94% of their 235 parti-

cipants had formed an online relationship of some kind (friendship or romantic in nat-

ure). The authors indicated that participants reported relationship breadth and depth,

commitment, predictability, and understanding of one another as being moderate to

high. Furthermore, nearly one third of their sample had progressed to in-person meet-

ings. Whitty and Gavin (2001) conducted interviews of 60 Internet users involved in

online relationships and reported that participants indicated ‘‘traditional’’ relationship

characteristics such as trust and commitment are equally important components in

relationships formed online. Baker (2002) examined case studies of eight couples that

met online to determine what characteristics led them to be successful after meeting

FTF and found that increased communication time and effective conflict management

skills were two factors that contributed to making the move to FTF. Wright (2004)

examined the relational maintenance strategies used by persons in nonromantic online

relationships and found that positivity and openness were the two most common stra-

tegies reported. These researchers are moving forward the study of online relationships,

yet further research into the burgeoning realm of online relationships is warranted as

personal relationships that develop online continue to increase and, in many cases,

move off-line (McKenna, Green, & Gleason, 2002).

Relationship Satisfaction

Relationship satisfaction, the degree to which an individual is content and satisfied

with his or her relationship, is a strong indicator of relationship length and success

in traditional FTF intimate relationships. Therefore, relationship satisfaction is

important not only for understanding successful online relationships but also as a

potential indicator of an online relationship that might effectively move to an

off-line, FTF relationship. Relationship satisfaction has been examined as both an

Online Relationship Satisfaction 155

individual and dyadic construct, and researchers have found that it is affected

by individuals’ perceptions of their partners’ various attitudes, behaviors, and

communication (Guerrero, 1994). For example, Burleson, Kunkel, and Birch

(1994) discovered that relationship satisfaction could in part be predicted by simi-

larity in communication values. Additionally, Neimeyer (1984) suggested that simi-

larity of interpersonal variables is a predictor of marital satisfaction.

Rusbult and Buunk (1993) found that couples that reported high relationship sat-

isfaction also reported higher levels of intimacy and commitment. In fact, numerous

studies that have examined the investment model show relationship satisfaction and

commitment are positively correlated whereas they are negatively correlated with

relationship alternatives. If an individual feels highly committed to an online partner

and is anticipating future interaction with the partner in an off-line context then per-

ceived commitment of the partner might influence satisfaction as the future success

of the off-line relationship may hinge upon the partner’s commitment to the

relationship as it stands. This is exacerbated by the knowledge that if the relationship

does progress to FTF, it may likely continue (at least for some time) as a long distance

relationship. This is because a large number of people who meet online are not geo-

graphically close and geographical distance may potentially lead to an increased need

for trust and commitment (see Rohlfing, 1995 for review).

Similarity

One variable that has been shown to influence relationship satisfaction is similarity,

the degree to which individuals perceive themselves as similar to others (e.g., Byrne,

1971; Duck, 1994). Barnes (2003) has suggested that similarity is important in online

relationships because it takes the place of proximity; people may not be able to be

close in physical location to someone with whom they are interacting online, yet they

can find others who share common interests and attitudes. Research has shown that

similarity attracts individuals to others with similar attitudes and backgrounds in

online social support groups that are based on specific interest and hobbies (e.g.,

Wright, 2000). According to Walther’s hyperpersonal model (1996), in the absence

of information not available online such as physical appearance, social status, and

so forth, interactants may make over-attributions about their own and their partners’

similarities and encourage responses that confirm this. Thus, if someone perceives

her=his online partner as highly similar, s=he may be interpersonally attracted to

the conversational partner and experience greater relationship satisfaction. In

addition, Barnes (2003) found that perceived similarity is a primary factor in decid-

ing whether to develop an online relationship.

Commitment

Commitment—the extent to which people in romantic relationships experience

relational cohesion (togetherness), exclusivity, and anticipated continuance of

the relationship (dedication)—is another factor shown to be important to FTF

156 T. L. Anderson & T. M. Emmers-Sommer

relationships (Rusbult, 1983). Researchers have found that commitment is linked to

relationship satisfaction (Sprecher, 1999). Rusbult (1980) argued for an investment

model of relationship development, positing that commitment is the result of indivi-

duals’ perceived alternatives to their current relationships, investment in the relation-

ships, and relationship satisfaction. Thus, consistent with Rusbult’s model, a person’s

perception of various factors in a relationship is central to that person’s relationship

satisfaction (and own level of commitment). In fact, Rusbult and Buunk (1993) stated

that ‘‘Highly committed individuals need their relationships, feel connected to their

partners and have a more extended, long-term time perspective regarding their rela-

tionships’’ (p. 180). Focusing on CMC, Parks and Floyd (1996) examined online

friendships formed in MUDs and reported that people experience moderate levels

of commitment with their online friends. It is possible that people online would

not only feel commitment toward online romantic partners but also that the level

of commitment would positively influence online relationship satisfaction.

Intimacy

A significant factor in the development of and satisfaction in relationships is inti-

macy. Social penetration theory posits that there is a significant alteration in patterns

of communication as intimacy develops in relationships (Altman & Taylor, 1973).

Furthermore, intimacy has been closely linked with communication satisfaction

(e.g., Hecht, 1978, 1984). Walther (1993, 1996) and others have explained that people

who engage in CMC tend to adapt to the low bandwidth of the context and use other

means to indicate nonverbal (including vocal) behaviors that connote intimacy.

Methods of adapting include the use of emoticons that can be used to convey inti-

macy in online contexts and to positively influence the development of online rela-

tionships (Utz, 2000; Walther & D’Addario, 2001). Walther (1996, 1997) reported

that even among those who had not met previously, people achieved higher levels

of intimacy through CMC than in similar FTF interactions. Corroborating Walther’s

findings, Hian, Chuan, Trevor, and Detenber (2004) examined how intimacy devel-

ops in FTF versus CMC contexts and reported that intimacy develops more quickly

in the CMC context due to the high frequency of interaction. Because intimacy is

likely to develop quickly and intensely in CMC due to the way persons process infor-

mation online in personal relationships, we can expect high levels of intimacy among

romantic online partners. In turn, we know that intimacy is a primary component in

the development of relationships; thus, heightened levels of intimacy may contribute

to relationship satisfaction in online romantic relationships.

Trust

According to uncertainty reduction theory, people will seek to gain information

about their relational partners in an effort to reduce uncertainty about those partners

(Berger, 1979; Berger & Calabrese, 1975). Because a central component of trust is a

relational partner’s behavioral predictability, a person in an intimate relationship will

Online Relationship Satisfaction 157

engage uncertainty-reducing strategies to gain knowledge of a partner’s relationship-

oriented behaviors. People high in uncertainty and subsequently low in trust possess

greater motivation to examine and assess their partner’s level of commitment than do

people high in certainty and trust (Holmes & Rempel, 1989). Although this lack of

trust can be caused by any number of personal and=or relational issues, people with

uncertainty and lacking in trust are inclined to react negatively to information about

their partners that they perceive to be unfavorable. According to Holmes and

Rempel, the very goal of uncertainty reduction is to ascertain a sense of security in

the relationship based on the partner’s level of attachment. Because online relation-

ships are forming and involve having trust in a relational partner (which is gained, in

part, through the development of intimacy), the degree to which one trusts an online

partner may affect level of relationship satisfaction. In addition, researchers have

recently found that strong levels of trust are not only possible when communicating

interpersonally online (Henderson & Gilding, 2004; Parvaneh, Lazar, & Preece, 2004)

but may be facilitated by CMC (Hardey, 2004).

Attributional confidence

Clatterbuck (1979) argued that increasing one’s attributional confidence is tantamount

to reducing uncertainty. Thus, a person has attributional confidence when s=he

perceives that information obtained about the relational partner is sufficient to explain

the partner’s current behaviors and predict future behaviors. When one does not feel

confidence about her=his ability to predict behaviors, s=he will experience uncertainty,

which is the inability to explain and to predict a relational partner’s actions (Berger &

Bradac, 1982). Uncertainty and its subsequent reduction have been posited to be a pri-

mary factor in the initiation and development of relationships (e.g., Berger & Bradac,

1982; Berger & Calabrese, 1975). In recent years, researchers have turned their attention

to the investigation of uncertainty in CMC environments (e.g., Pratt, Wiseman, Cody,

& Wendt, 1999). Tidwell and Walther (2002) found interactants using CMC tend to

adapt their uncertainty management strategies to the context and engage in more inter-

active strategies and fewer passive and active strategies than do persons communicating

FTF. Key elements in uncertainty reduction in relationships such as attraction and

nonverbal affiliative expressiveness may not take the same role in relationships where

partners do not interact FTF. Uncertainty or degree of predictability of a partner’s level

of commitment and feelings of intimacy could affect relationship satisfaction. In CMC

contexts the possibility of feedback delays and lack of social and visual cues may lead to

higher uncertainty due to the inability to reduce uncertainty about the partner’s

behavior (Parks & Floyd, 1996). Thus, level of uncertainty=certainty may influence

one’s relationship satisfaction; we might expect that as one’s attributional confidence

goes up, so will relationship satisfaction.

Communication satisfaction

According to the social exchange perspective, relationships continue to develop as

rewards exceed costs (Thibaut & Kelley, 1959). Because communication is a building

158 T. L. Anderson & T. M. Emmers-Sommer

block of relationships (Duck & Pittman, 1994), satisfying interpersonal communication

should aid in relationship development (Hecht, 1978). Satisfying communication

occurs when one’s expectations for the interaction are met and fulfilled. In addition,

when a person feels understood by her or his partner, this person experiences greater

relationship happiness (e.g., Cahn, 1983). Perceptions of understanding and success

in communication interactions contribute to communication satisfaction. In an

examination of FTF relationships, Emmers-Sommer (2004) found that communi-

cation satisfaction contributed to relational closeness and satisfaction. It is of interest

to examine this pattern in an online context as well.

Research has shown that these aforementioned relational variables—similarity, com-

mitment, intimacy, trust, attributional confidence, and communication satisfaction—

influence relational outcomes and often predict relationship satisfaction. For example,

Gottman (1999) reported that intimacy, relationship satisfaction, and communication

are positively related. However, it is unknown how these variables affect relationship

satisfaction in online romantic relationships. Following Walther’s premise that online

interactants are prone to a engaging in a cyclical process in which they selectively edit

messages and information when presenting themselves, make positive over-attributions

about CMC partners and increase levels of self-disclosure, persons in online romantic

relationships may have heightened perceptions of relational variables that will posi-

tively influence online relationship satisfaction. In addition, it is important to examine

which relational variables function together to predict online relationship satisfaction

because satisfaction predicts the stability of a relationship to large extent (Rohlfing,

1995). Therefore, we posit the following question:

RQ1: To what degree do similarity, commitment, intimacy, trust, attributionalconfidence, and communication satisfaction predict relationship satisfactionfor individuals in online romantic relationships?

In addition, prior research indicates that CMC becomes more personal over time

and, as interaction increases, perceptions of CMC partners become positively skewed

(Hian, Chuan, Trevor, & Detenber, 2004; Walther, 1996). However, we do not know

how perceptions of similarity, commitment, intimacy, trust, attributional confidence,

and communication satisfaction are affected by amount of communication time. We

may expect that those people in online relationships who spend more time com-

municating may perceive their relationships differently than those who communicate

fewer hours. However, because CMC can become intimate so quickly, differences

may not be as extensive. Additionally, relationship length may positively affect per-

ceptions as well because if hyperpersonal interaction is occurring then over time

people may intensify their idealized notions of their partners. Thus:

RQ2: For individuals in online romantic relationships do perceptions of simi-larity, commitment, intimacy, trust, attributional confidence, and com-munication satisfaction differ depending on relationship length?

RQ3: For individuals in online romantic relationships do perceptions of simi-larity, commitment, intimacy, trust, attributional confidence, and com-munication satisfaction differ depending on amount of communication?

Online Relationship Satisfaction 159

Method

Participants and Sampling Protocol

One hundred-fourteen (N ¼ 114) voluntary participants who were in exclusively

online-based romantic relationships completed a Web-based survey. Participants

had not met their romantic partner in person nor had spoken to them on the tele-

phone. To solicit participants, a researcher entered online chat rooms that focus

on online friendships, relationships, and long-distance relationships1 to request

volunteers. Additionally, the researcher posted messages asking for volunteers in

Usenet romance-related men’s and women’s newsgroups.

The participants were demographically diverse and, although the majority was

from the United States, they represented many countries.2 The sample was comprised

of 32 (28.1%) men and 82 (71.9%) women, with ages ranging from 18 to 62

(M ¼ 31.49, SD ¼ 9.88). Participants’ levels of education ranged from some high

school to a doctorate degree, with most participants having earned a bachelor’s

degree. Ninety participants (78.9%) met their online romantic partners serendipi-

tously in a synchronous communication environment (e.g., chatting), 10 (8.8%)

participants met their partners serendipitously in a listserv or bulletin board, and

14 (12.3%) participants met their partners through an online dating service. The

average length of relationships was 27.17 weeks (SD ¼ 20.03).

Measures

Similarity

The Measure of Perceived Homophily (McCroskey, Richmond, & Daly, 1975) was

used to assess the degree to which participants perceive they are similar to their

respective online relational partners. The eight item, seven-point semantic differential

scale assesses two dimensions, attitude and background homophily, and has been

shown to be reliable in past research (e.g., Elliot, 1979). The current study yielded

Cronbach’s alphas ¼ .79 for both attitude and background dimensions.

Commitment

Perception of both online and off-line relational alternatives was conceptualized as

the degree to which one possesses alternatives (other relational partners, either on-

or off-line) to the current relationship. Relational commitment was measured using

eight seven-point, Likert-type scale items adapted from Rusbult’s (1980) tests of her

investment model. The scale assesses one’s dedication to the relationship and one’s

perceived relational alternatives, which are fundamental to the notion of commit-

ment. Previous research for this measure has demonstrated a reliability of .90 (Cloven

& Roloff, 1993). Cronbach’s alpha ¼ .92 in the current study.

Intimacy

Feelings of intimacy were assessed using Miller’s Social Intimacy scale (MSIS) (Miller

& Lefcourt, 1982). Baxter (1988) reported that this scale yielded high reliability scores

160 T. L. Anderson & T. M. Emmers-Sommer

and in the current study the scale yielded a Cronbach’s alpha ¼ .90. The measure

contains 17 items measured on a 10-point Likert-type scale that assess degree and fre-

quency of perceived closeness as achieved through behaviors and communication

interactions. The MSIS taps into the dimension of psychological intimacy only, which

is most appropriate for this study given that participants are not geographically close

to partners.

Trust

The Dyadic Trust Scale (Larzelere & Huston, 1980) was used to measure the parti-

cipants’ degree of trust for their respective partners. The measure contains eight,

seven-point Likert-type items. Larzalere and Huston reported an alpha reliability

of .93, and Baxter (1988) has argued that, based on evidence from prior studies,

the Dyadic Trust Scale has greater construct validity and internal reliability than

other trust measures. Cronbach’s alpha ¼ .90 in the current study.

Attributional confidence

The short version of the Attributional Confidence Scale (CL7) (Clatterbuck, 1979)

was used to assess participants’ perceived level of certainty about their online rela-

tionships. Specific to this investigation, the CL7 was utilized to measure the degree

to which individuals could make attributions with confidence (i.e., with certainty)

about occurrences in their online relationships. Certainty is measured on a 0% to

100% scale. This short, proactive version of the scale—which focuses on one’s con-

fidence in making attributions before events occur instead of retroactively making

attributions—is preferred over the longer version of the scale (CL65) due to ease

of administration. Prior research has yielded reliabilities of .76 to .97 (e.g., Clatter-

buck, 1979). Cronbach’s alpha ¼ .89 in the current study.

Communication satisfaction

Interpersonal communication satisfaction was conceptualized as ‘‘the emotional

reaction to communication which is both successful and expectation fulfilling’’

(Hecht, 1984, p. 201). This predictor variable was assessed using a shortened version

of Hecht’s (1978) seven-point Likert-type measure of communication satisfaction.

This eight-item abridged version has been factor analyzed and shown to be reliable

(a ¼ .93) in previous cross-sectional and longitudinal studies (VanLear, 1988,

1991) and had an alpha of .96 in the current study.

Relationship satisfaction

Relationship satisfaction is the degree to which an individual is content with his or

her current relationship. To assess relationship satisfaction the researchers used a

version of Norton’s (1983) Quality Marriage Index (QMI) adapted for persons in

(nonmarital) online romantic relationships. The QMI is a six-item Likert-type scale.

Online Relationship Satisfaction 161

Norton’s measure is considered by many to be an improvement on early measures of

relationship satisfaction and has yielded Cronbach alpha scores ranging from .88 to

.96 (e.g., Baxter, 1988; VanLear, 1991). Additionally, the measure has remained

reliable in previous studies when adapted for nonmarried persons (VanLear, 1991).

Cronbach’s alpha ¼ .95 in the current study.

Relationship length

Relationship length was measured by asking participants to report how many weeks

they had been involved with their current online romantic partner. Length ranged

from 3 to 53 weeks with an average of 27.17 weeks (SD ¼ 20.03).

Amount of online communication

The time spent communicating online was measured by asking participants how

many hours per week, in general, they communicated online with their partners

including all forms of communication (e.g., sending and reading e-mail, interacting

in a MUD). Communication time ranged from 1 to 40 hours a week with an average

17.64 hours (SD ¼ 14.20). ‘‘Amount’’ was operationalized not in terms of ‘‘how

often’’; rather, it was operationalized as ‘‘how much’’.3

Results

All tests were conducted at the p < .05 level. Only significant results are reported and

addressed in the discussion.

The first research question asked what relational variables predicted relationship

satisfaction for individuals in online romantic relationships. To test RQ1, we conduc-

ted a forced entry linear regression, which showed that the predictor variables (atti-

tude similarity, background similarity, commitment, intimacy, trust, attributional

confidence, and communication satisfaction4) accounted for 85% of the variance in

online relationship satisfaction, R2 ¼ .85, adjusted R2 ¼ .84, F (7, 106) ¼ 98.96,

p < .001. Results of the regression model indicated that three predictors—intimacy,

trust, and communication satisfaction—were significant at an alpha of less than .01.

Standardized beta coefficients, t-values, and partial correlations (holding the effects

of all other predictor variables constant) for these three variables are listed in Table 1.5

The second research question asked whether perceptions of similarity (attitude

and background), commitment, intimacy, trust, attributional confidence, and com-

munication satisfaction differ depending on relationship length. The authors conduc-

ted analyses of variance to examine whether the perceived levels of the reported

relational variables differed based on length of relationship (short, average, long).

The ANOVA scores were significant for attitude similarity F (2, 111) ¼ 4.58,

p ¼ .01, g2 ¼ 0.8, intimacy F (2, 111) ¼ 15.23, p < .001, g2 ¼ 0.22, trust F (2,

111) ¼ 10.37, p < .001, g2 ¼ 0.16, and attributional confidence, F (2, 111) ¼ 5.65,

p < .01, g2 ¼ 0.09. Multiple comparison procedures were conducted using the Tukey

162 T. L. Anderson & T. M. Emmers-Sommer

HSD test. Results indicate that levels of perceived attitude similarity differed signifi-

cantly between those persons whose relationship length was average and those

persons who were in a lengthy online relationship. For perceived intimacy, levels

differed significantly between people in long relationships and average-length

relationships, and between people in average-length relationships and short relation-

ships. Specifically, those who had been in their online relationships a greater amount

of time reported greater levels of intimacy. For trust, there were significant differences

between those who had been together the longest and those who were together an

average length of time. There were also differences in trust levels between those

who had the longest and shortest relationships. Finally, regarding attributional con-

fidence, means differed significantly between those persons who had been in their

online relationships the shortest length of time and those who had been involved

the longest. Means and standard deviations for attitude similarity, intimacy, trust,

and attributional confidence are listed in Table 2.

The third research question asked whether perceptions of similarity (attitude and

background), commitment, intimacy, trust, attributional confidence, and communi-

cation satisfaction differ depending on amount of time spent communicating with

one’s partner. Again, the authors conducted a series of ANOVAs to examine whether

the levels of the reported relational variables differed based on time spent communi-

cating with one’s partner (low, moderate, and high). The tests were significant for

attitude similarity F (2, 111) ¼ 24.07, p < .001, g2 ¼ 0.30, background similarity

F (2, 111) ¼ 8.33, p < .001, g2 ¼ 0.13, commitment F (2, 111) ¼ 27.93, p < .001,

g2 ¼ 0.34, intimacy F (2, 111) ¼ 17.19, p < .001, g2 ¼ 0.24, trust F (2, 111) ¼19.05, p < .001, g2 ¼ 0.26, attributional confidence F (2, 111) ¼ 7.40, p ¼ .001,

g2 ¼ 0.19, and communication satisfaction F (2, 111) ¼ 7.52, p ¼ .001, g2 ¼ 0.20.

Post hoc tests for the analyses of variance indicate there are significant differences

in perceptions of attitude similarity. Specifically, low and high communicators, as

well as moderate and high communicators, were significantly different from one

another with the higher communication groups reporting greater perceived attitude

similarity. For background similarity, moderate communicators differed significantly

from both low and high communicators, such that the moderate communicators

reported higher levels of perceived background similarity. Regarding commitment,

low and moderate communicators, and moderate and high communicators, reported

significantly different commitment levels; as communication time went up so did

Table 1 Standardized Beta Coefficients, t-Values, Partial Correlations, Unstandardized

Beta Coefficients and Confidence Intervals for Main Predictors of Relationship

Satisfaction

Variable ß t value Sig. Partial r B Lower CI Upper CI

Trust .377 4.112 .000 .369 .426 .220 .631

Intimacy .328 3.645 .000 .332 .477 .217 .736

ComSat .442 7.609 .000 .593 .800 .592 1.009

Online Relationship Satisfaction 163

perceived commitment. Perceptions of intimacy differed among all groups. High

communicators reported significantly more intimacy than did moderate or low com-

municators, and moderate communicators reported significantly less intimacy than

low communicators. For trust, both low and moderate communicators reported sig-

nificantly lower levels of trust than did high communicators. Levels of attributional

confidence differed significantly between those persons who communicated at moder-

ate and high levels, with those communicating a greater amount reporting higher attri-

butional confidence. Last, regarding communication satisfaction, both the low and

moderate groups reported significantly lower satisfaction than did the high communi-

cation group. Means and standard deviations for these variables are listed in Table 3.

Discussion

The purpose of this study was to determine key predictors of relationship satisfaction

in online romantic relationships. Specifically, to what extent do similarity, commit-

ment, intimacy, trust, attributional confidence, and communication satisfaction

Table 2 Means and Standard Deviations for Relationship Variables

with Significant Differences Based on Relationship Length�

Variable

Relationship length Mean SD

Attitude similarity

Short 5.57 1.35

Average 5.18��� 1.39

Long 6.04��� 1.05

Intimacy

short 8.50�� 1.08

Average 8.93�� .55

Long 9.47�� .56

Trust

Short 5.62 1.32

Average 5.97 1.10

Long 6.66���� .42

Attributional confidence

Short 80.17��� 17.56

Average 85.86 7.14

Long 90.15��� 12.2

�n sizes for each respective relationship group are as follows: short ¼ 34, average ¼ 40,

long ¼ 40.��each group significantly different from the other at p < .05.���groups significantly different from one another at p < .05.����group significantly different from other groups at p < .05.

164 T. L. Anderson & T. M. Emmers-Sommer

affect and predict the degree to which a person feels relationally satisfied when

involved with another person romantically online. In addition, we were interested

in examining whether differences existed among these variables based on online

relationship length and amount of time online partners communicated with each

Table 3 Means and Standard Deviations for Relationship Variables

with Significant Differences Based on Amount of Communication

Variable

Amt. of com time Mean SD

Attitude similarity

Low 4.78 .19

Moderate 5.33 .18

High 6.48���� 1.70

Background similarity

Low 5.24 .25

Moderate 4.00���� .24

High 5.13 .23

Commitment

Low 4.70�� 1.80

Moderate 5.80�� 1.26

High 6.81�� .30

Intimacy

Low 8.41�� .83

Moderate 9.02�� .80

High 9.42�� .61

Trust

Low 5.47 1.10

Moderate 5.92 1.22

High 6.78���� .39

Attributional confidence

Low 84.37 7.83

Moderate 80.59��� 17.54

High 91.16��� 9.94

Com satisfaction

Low 6.45 .56

Moderate 6.47 .98

High 6.94���� .11

�n sizes for each respective amount of communication group are as follows: low ¼ 33,

moderate ¼ 38, high ¼ 43.��each group significantly different from the other at p < .05.���groups significantly different from one another at p < .05.����group significantly different from other groups at p < .05.

Online Relationship Satisfaction 165

other. The following section addresses some theoretical implications of this research,

limitations, and suggestions for future research.

Results of our analysis reveal that intimacy, trust, and communication satisfaction

significantly predicted online relationship satisfaction. Although it was surprising

that some of the predictor variables did not significantly predict satisfaction, this

finding does reveal that some important FTF relational components also contributed

to satisfaction in online romantic relationships. When evaluating the role of trust in

predicting online relationship satisfaction, because people rely on their perceptions of

their partners when gauging partner’s trustworthiness, the hyperpersonal model may

account for the relatively high levels of trust in this study and the effect of trust on

relationship satisfaction. Additionally, those who are trusting use this trust to frame

partner’s behaviors (Holmes & Rempel, 1989). Thus, interpretations of one’s partner

may become a function of selective perception by which a partner’s behaviors are

interpreted as consistent with one’s positive expectations (Murray & Holmes,

1993). Furthermore, one’s opportunity for an ‘‘enhanced performance’’ online and

the development of a trustworthy reputation are two main components of online

trust (Henderson & Gilding, 2004). Hyperpersonal interaction allows for such

enhanced interactions online that in turn may facilitate a favorable reputation as per-

ceived by one’s partner. Additionally, trust and intimacy are linked closely; as part-

ners grow closer and depth increases, trust develops and as trust increases, so do

levels of intimacy. Wright (2004) found that openness was one of two most com-

monly used maintenance strategies for online relationships, which suggests that rela-

tional behaviors of persons in online relationships tend to facilitate intimacy, and

research has found intimacy develops quickly online (Hian et al., 2004; Walther,

1997). Furthermore, the role of intimacy in predicting relationship satisfaction in this

study is consistent with a wealth of personal relationship research that indicates

intimacy is a key component of relationship and marital satisfaction (e.g., Feeney,

Noller, & Ward, 1997; Hassebrauck & Fehr, 2002).

It is not surprising that communication satisfaction predicted relationship satis-

faction. Communication is a central component of establishing and developing

relationships (e.g., Duck & Pittman, 1994), and in online relationships simple, every-

day interaction allows partners to maintain their relationships (Rabby & Walther,

2003). In essence, given online partners’ inability to ‘‘go out,’’ have physical contact,

or experience other components related to physical presence that are enmeshed in

FTF romantic unions, the online communication is the relationship. Furthermore,

researchers have found that communication satisfaction is positively correlated with,

and predictive of, FTF relationship satisfaction (e.g., Emmers-Sommer, 2004;

Guerrero, 1994). Additionally, persons lacking other cues in CMC are likely to attend

more closely to the textual messages sent by one’s partner, while at the same time the

CMC partner is likely editing and presenting oneself carefully, thus leading to the

‘‘idealized’’ perceptions of one’s communicative partner (Walther, 1996). Thus, fol-

lowing hyperpersonal theory, CMC provides an immense opportunity for perceived

communication satisfaction. Because an online relationship is wholly dependent upon

communication (albeit primary textual, such as chat and e-mail), communication

166 T. L. Anderson & T. M. Emmers-Sommer

satisfaction is necessary for relationship satisfaction as there is little else on which to

base perceptions of the relationship; if communication ceases, so does the relation-

ship. Additionally, hyperpersonal interaction afforded by CMC may have enhanced

perceptions of one’s communication with an online partner by facilitating idealized

perceptions of that partner and her=his communication skills (Walther, 1996).

Results also indicated that individuals who communicated a greater amount of

time per week reported higher communication satisfaction with their partners than

those who communicated with their partners a fewer number of hours per week. This

finding is encouraging as it relates to CMC. Specifically, in an examination of what

best predicted relational satisfaction and intimacy—quality or quantity time—

Emmers-Sommer (2004) found that quality of communication better predicted those

outcomes than quantity of communication. Although a variety of mediums were

evaluated, results indicated that FTF communication was key for quantity of com-

munication. The findings of the present study, however, indicate that participants

were satisfied with their online communication and the relational outcomes associa-

ted with CMC.6 Length of relationship did not account for as many differences in

perceptions as did amount of communication; people who had been involved for

longer periods of time with their online romantic partners reported greater levels

of intimacy, trust, and attributional confidence than did those who had been dating

online for shorter periods of time. Attributional confidence levels also differed

according to amount of communication time, with those persons who communi-

cated a greater amount reporting higher attributional confidence levels. Thus,

amount of communication time (accounting for significant differences in attitude

and background similarity, commitment, intimacy, trust, attributional confidence,

and communication satisfaction) had a greater impact on perceptions than did length

of relationship (accounting for differences in intimacy, trust, and attributional con-

fidence only).

Increased communication time with online partners may have led to participants

forming idealized=heightened perceptions of similarity, commitment, intimacy, trust,

attributional confidence, and communication satisfaction because CMC interaction

allows people to engage in hyperpersonal behaviors. That is, participants were able

to attend to cues that confirmed their desired perceptions (cues that were carefully

edited by their respective relational partners) and, due to information lacking in

CMC, they did not have access to cues that may have contradicted those idealized

perceptions. These findings are consistent with prior research that shows frequency

of CMC affects perceptions of online partners (Walther, 1996; Wright, 2004).

Additionally, intimacy, trust, and attributional confidence may be greater for those

in longer relationships because, when communicating online, it takes longer for

socioemotional indicators to manifest themselves (Walther, 1992, 1993; Walther &

Burgoon, 1992).

One limitation of the current study was the use of a nonrandom convenience

sample of persons in online romantic relationships, largely because it is impossible

to obtain a list of the population of persons involved in online romantic

relationships. In fact, because there is often a stigma for people in online relationships

Online Relationship Satisfaction 167

(Wildermuth, 2001), people may be hesitant to identify themselves and participate

in related research. The sample may have affected the relatively high levels of satisfac-

tion reported by participants because it is possible that only those persons who

were highly satisfied with their online relationships chose to participate. That is,

self-selection might have been an issue. Another limitation was the use of a one shot

cross-sectional design and the lack of a FTF comparison group. As it is worthwhile to

explore whether perceptions in CMC differ from FTF (Parks & Roberts, 1998), a

comparison of online and FTF relationship predictors is warranted to assess the

degree to which predictors found in this study were influenced by the medium.

Future researchers could benefit from investigating the ways in which intimacy,

trust, and communication satisfaction mutually influence one another in hyperper-

sonal interaction and how they work collectively to predict satisfaction in online

romantic relationships. Additionally, researchers should examine whether predictors

of relationship satisfaction in nonromantic relationships differ from the predictors

noted here and whether hyperpersonal communication functions differently in

romantic versus nonromantic relationships. Perhaps most importantly, future

research should explore how perceptions of relationships formed via hyperpersonal

communication affect perceptions once partners have met FTF and the extent to

which these perceptions predict a successful move from an online to a FTF romantic

relationship. Because many online relationships become long-distance relationships

after moving to FTF, it may be fruitful to investigate how predictors of relationships

satisfaction affect relationships and whether predictors of satisfaction change as these

relationships move from online to primarily Internet-based (geographically sepa-

rated) relationships (Wright, 2004), and from primarily Internet-based relationships

to fully FTF (geographically close) relationships. Specifically, future research may

focus on the extent to which perceptions of relational variables, established through

hyperpersonal interaction, carry over to the relationships once they move off-line. Of

additional importance and interest is whether positively skewed perceptions of online

partners are maintained or disconfirmed if the relationship moves off-line; and, if

disconfirmed, what this means for the future of relationships initiated online that

progress off-line.

Notes

[1] Using a list of all chat rooms available on AOL that dealt with online friendship and

romance, and long-distance relationships (e.g., social support and sexual chat rooms, for

example, were not used), every 30th chat room was visited by the researcher for a total of

15 chat rooms.

[2] Country of origin break down for participants was as follows: United States (n ¼ 77,

67.5%), Canada (n ¼ 14, 12.3%), Australia (n ¼ 8, 7%), France (n ¼ 3, 2.6%), Germany

(n ¼ 2, 1.8%), Italy (n ¼ 1, .9%), the Netherlands (n ¼ 3, 2.6%), New Zealand (n ¼ 1,

.9%), and the United Kingdom (n ¼ 3, 2.6%).

[3] Initially, we examined frequency of interaction as a predictor variable as well, but the vari-

able suffered from lack of variability. Specifically, the mean, median, and mode were the

same (7 on a scale of 1 to 7, with 7 ¼ days a week). As a result, we removed frequency

168 T. L. Anderson & T. M. Emmers-Sommer

of interaction from the current analyses. However, consistent with Walther’s work, we

recognize frequency of interaction to be an important variable and one worthy of inclusion

in future studies.

[4] We used criteria established by Stevens (1996) to test for high multicollinearity. These

criteria included the examination of a correlation matrix for any bivariate correlation over

.80 and the examination of the predictors’ variance inflation factors for any variance

inflation factor (VIF) over 10.00, which identified one correlation higher than .80; trust

and intimacy were correlated at .842 (p < .001). However, Meyers (1990) argues there is

need for concern (and subsequent variable deletion) if a VIF exceeds 10 and, because neither

VIF was above ten (trust VIF ¼ 5.89; intimacy VIF ¼ 5.86), both distinct variables were

retained.

[5] Although beta coefficients indicate a positive relationship among trust, intimacy, and

communication satisfaction, due to the prior decision rules established for dealing with mul-

ticollinearity, variables were kept as distinct entities and not combined into any composite

variables.

[6] It should be taken into consideration that Emmers-Sommer (2004) did not collect data in an

online forum, whereas the current study involves an online collection (i.e., participants

might self-select medium based on preferences).

References

Altman, I. & Taylor, D. (1973). Social penetration theory. New York: Holt, Rinehart & Winston.

Anderson, T. L. (2005). Relationships among internet attitudes, internet use, romantic beliefs, and

perceptions of online romantic relationships. Cyberpsychology & Behavior, 8, 521–531.

Baker, A. (2002). What makes an online relationship successful? Clues from couples who met in

cyberspace. CyberPsychology & Behavior, 5, 364–375.

Barnes, S. (2003). Computer-mediated communication: Human-to-human communication across the

Internet. Boston: Allyn & Bacon.

Baxter, L. A. (1988). Dyadic personal relationships: Measurement options. In C. H. Tardy (Ed.),

A handbook for the study of human communication: Methods and instruments for observing,

measuring, and assessing communication processes (pp. 193–283). Norwood, NJ: Ablex.

Berger, C. R. (1979). Beyond initial interaction: Uncertainty, understanding, and the development

of interpersonal relationships. In H. Giles & R. N. St. Clair (Eds.), Language and social

psychology (pp. 122–144). Oxford: Basil Blackwell.

Berger, C. R. & Bradac, J. J. (1982). Language and social knowledge: Uncertainty in interpersonal rela-

tions. London: Arnold.

Berger, C. R. & Calabrese, R. J. (1975). Some explorations in initial interaction and beyond: Toward

a developmental theory of interpersonal communication. Human Communication Research,

1, 99–112.

Burleson, B. R., Kunkel, A. W., & Birch, J. D. (1994). Thoughts about talk in romantic relation-

ships: Similarity makes for attraction (and happiness, too). Communication Quarterly, 42,

259–273.

Byrne, D. (1971). The attraction paradigm. New York: McGraw-Hill.

Cahn D. D. (1983). Relative importance of perceived understanding in initial interaction and devel-

opment of interpersonal relationships. Psychological Reports, 52, 923–929.

Chenault, B. G. (1998, May). Developing personal and emotional relationships via computer-

mediated communication. Retrieved April 18, 2000 on the World Wide Web: http://

www.december.com/ cmc/mag/1998/may/chenault.html

Clatterbuck, G. W. (1979). Attributional confidence and uncertainty in initial interaction. Human

Communication Research, 5, 147–157.

Online Relationship Satisfaction 169

Cloven, D. H. & Roloff, M. E. (1993). The chilling effect of complaints in intimate relationships:

Aggressive potential on the expression of complaints in intimate relationships. Communi-

cation Monographs, 60, 199–219.

Culnan, M. J. & Markus, M. L. (1987). Information technologies. In F. Jablin, L. L. Putnam,

K. Roberts, & L. Porter (Eds.), Handbook of organizational communication (pp. 420–443).

Newbury Park, CA: Sage.

Draft, R. L., Lengel, R. H., & Trevino, L. K. (1987). Message equivocality, media selection, and man-

ager performance: Implication for information systems. MIS Quarterly, 11, 355–366.

Duck, S. W. (1994). Meaningful relationships: Talking, sense, and relationships. Newbury Park, CA:

Sage.

Duck, S. W. & Pittman, G. (1994). Social and personal relationships. In M. L. Knapp & G. R. Miller

(Eds.), Handbook of interpersonal communication (pp. 676–695). Thousand Oaks, CA: Sage.

Elliot, S. (1979). Perceived homophily as a predictor of classroom learning. Communication Year-

book, 3, 585–602.

Emmers-Sommer, T. M. (2004). The effect of communication quality and quantity indicators on

intimacy and relational satisfaction. Journal of Social and Personal Relationships, 21, 399–411.

Emmers-Sommer, T. M. (2005). Non-normative relationships: Is there a norm of (non) normativ-

ity? Western Journal of Communication, 69(1), 1–4.

Feeney, J. A., Noller, P., & Ward, C. (1997). Marital satisfaction and spousal interaction. In

R. J. Sternberg & M. Hojjat (Eds.), Satisfaction in close relationships (pp. 160–189). New York:

Guilford.

Gottman, J. M. (1999). The marriage clinic: A scientifically-based marital therapy. New York:

W. W. Norton & Company.

Guerrero, L. K. (1994). ‘‘I’m so mad I could scream’’: The effects of anger expression on relational

satisfaction and communication competence. Southern Communication Journal, 59, 135–141.

Hardey, M. (2004). Mediated relationships. Information Communication & Society, 7, 207–222.

Hassebrauck, M. & Fehr, B. (2002). Dimensions of relationship quality. Personal Relationships, 9,

253–270.

Hecht, M. L. (1978). The conceptualization and measurement of interpersonal communication

satisfaction. Human Communication Research, 4, 253–264.

Hecht, M. L. (1984). Satisfying communication and relationship labels: Intimacy and length of

relationship as perceptual frames of naturalistic conversations. Western Journal of Communi-

cation, 48, 201–216.

Henderson, S. & Gilding, M. (2004). ‘‘I’ve never clicked this much with anyone in my life’’: Trust

and hyperpersonal communication in online friendships. New Media & Society, 6, 487–506.

Hian, L. B., Chuan, S. L., Trevor, T. M. K., & Detenber, B. H. (2004). Getting to know you: Explor-

ing the development of relational intimacy in computer-mediated communication. Journal

of Computer-Mediated Communication, 9(3). Retrieved October 7, 2004 from http://www.

ascusc.org/jcmc/vol9/issue3/detenber.html

Holmes, J. G. & Rempel, J. K. (1989). Trust in close relationships. In C. Hendrick (Ed.), Close rela-

tionships: Review of personality and social psychology, 10. Newbury Park, CA: Sage.

Kellerman, K. (1986). Anticipation of future interaction and information exchange in initial inter-

action. Human Communication Research, 13, 41–75.

Larzelere, R. E. & Huston, T. L. (1980). The dyadic trust scale: Toward understanding interpersonal

trust in close relationships. Journal of Marriage and the Family, 42, 595–604.

Lea, M. & Spears, R. (1995). Love at first byte? Building personal relationships over computer

networks. In J. T. Wood & S. Duck (Eds.), Under-studied relationships: Off the beaten track

(pp. 197–233). Thousand Oaks, CA: Sage.

McCroskey, J. C., Richmond, V. P., & Daly, J. A. (1975). The development of a measure of

perceived homophily in interpersonal communication. Human Communication Research,

1, 323–332.

170 T. L. Anderson & T. M. Emmers-Sommer

McKenna, K. Y. A., Green, A. S., & Gleason, M. E. J. (2002). Relationship formation on the Internet:

What’s the big attraction? Journal of Social Issues, 58, 9–31.

Merkle, E. R. & Richardson, R. A. (2000). Digital dating and virtual relating: Conceptualizing

computer-mediated romantic relationships. Family Relations, 49, 187–192.

Meyers, R. (1990). Classical and modern regression with applications (2nd ed.). Boston: Duxbury

Press.

Miller, R. S. & Lefcourt, H. M. (1982). The measurement of social intimacy. Journal of Personality

Assessment, 46, 514–518.

Murray, S. L. & Holmes, J. G. (1993). Seeing virtues in faults: Negativity and the transformation of

interpersonal narratives in close relationships. Journal of Personality and Social Psychology, 65,

707–722.

Myers, D. (1987). ‘‘Anonymity is part of the magic’’: Individual manipulation of computer-

mediated contexts. Qualitative Sociology, 10, 251–266.

Neimeyer, G. J. (1984). Cognitive complexity and marital satisfaction. Journal of Social and Clinical

Psychology, 2, 58–263.

Norton, R. (1983). Measuring marital quality: A critical look at the dependent variable. Journal of

Marriage and the Family, 45, 141–151.

Parks, M. R. & Floyd, K. (1996). Making friends in cyberspace. Journal of Communication, 46,

80–97.

Parks, M. R. & Roberts, L. D. (1998). ‘‘Making MOOsic’’: The development of personal relation-

ships online and a comparison to their off-line counterparts. Journal of Social and Personal

Relationships, 15, 517–537.

Parvaneh, J. F., Lazar, J., & Preece, J. (2004). Empathy and online interpersonal trust: A fragile

relationship. Behavior & Information Technology, 23, 97–106.

Pratt, L., Wiseman, R. L., Cody, M. L., & Wendt, P. F. (1999). Interrogative strategies and infor-

mation exchange in computer-mediated communication. Communication Quarterly, 47,

46–66.

Rabby, M. K. & Walther, J. B. (2003). Computer-mediated communication impacts on relationship

formation and maintenance. In D. Canary & M. Dainton (Eds.), Maintaining relationships

through communication: Relational, contextual, and cultural variations (pp. 141–162).

Mahwah, NJ: Lawrence Erlbaum Associates.

Rohlfing, M. E. (1995). ‘‘Doesn’t anybody stay in one place anymore?’’: An exploration of the

under-studied phenomenon of long-distance relationships. In J. T. Woods and S. Duck

(Eds.), Under-studied relationships: Off the beaten track (pp. 173–196). Thousand Oaks,

CA: Sage.

Rumbough, T. (2001). The development and maintenance of interpersonal relationships through

computer-mediated communication. Communication Research Reports, 18, 223–230.

Rusbult, C. E. (1980). Commitment and satisfaction in romantic associations: A test of the invest-

ment model. Journal of Experimental Social Psychology, 16, 172–186.

Rusbult, C. E. (1983). A longitudinal test of the investment model: The development (and deterio-

ration) of satisfaction and commitment in heterosexual involvements. Journal of Personality

and Social Psychology, 45, 101–117.

Rusbult, C. E. & Buunk, B. P. (1993). Commitment processes in close relationships: An interdepen-

dence analysis. Journal of Social and Personal Relationships, 10, 175–205.

Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunication. London:

John Wiley.

Spears, R. & Lea, M. (1994). Panacea or panopticon: The hidden power in computer-mediated

communication. Communication Research, 21(4), 427–459.

Sprecher, S. (1999). ‘‘I love you more today than yesterday’’: Romantic partners’ perceptions of

changes in love and related affect over time. Journal of Personality and Social Psychology,

76, 46–53.

Online Relationship Satisfaction 171

Sproull, L. & Kiesler, S. (1991). Connections: New ways of working in networked organization.

Cambridge, MA: MIT Press.

Stevens, J. (1996). Applied multivariate statistics for the social sciences. Mahwah, NJ: Erlbaum.

Thibaut, J. W. & Kelley, H. H. (1959). The social psychology of groups. New York: Wiley.

Tidwell, L. C. & Walther, J. B. (2002). Computer-mediated communication effects on disclosure,

impressions and interpersonal evaluations: Getting to know one another a bit at a time.

Human Communication Research, 28(3), 317–348.

Utz, S. (2000). Social information processing in MUDs: The development of friendships in virtual

worlds. Journal of Online Behavior, 1(1). Retrieved Aug. 28, 2003 from http://www.behavior.

net/JOB/v1n1/utz.html

VanLear, C. A. (1988, July). Perceived openness of self and other across relationships with differential

growth trajectories: A longitudinal study. Paper presented at the Fourth International Confer-

ence on Personal Relationships, Vancouver, Canada.

VanLear, C. A. (1991). Testing a cyclical model of communicative openness in relational develop-

ment: Two longitudinal studies. Communication Monographs, 58, 337–361.

Walther, J. B. (1992). Interpersonal effects in computer-mediated interaction: A relational perspec-

tive. Communication Research, 19, 52–90.

Walther, J. B. (1993). Impression development in computer-mediated interaction. Western Journal

of Communication, 57, 381–398.

Walther, J. B. (1996). Computer-mediated communication: Impersonal, interpersonal, and hyper-

personal interaction. Communication Research, 23, 3–43.

Walther, J. B. (1997). Group and interpersonal effects in international computer-mediated collab-

oration. Human Communication Research, 23, 342–369.

Walther, J. B. & Burgoon, J. K. (1992). Relational communication in computer-mediated interac-

tion. Human Communication Research, 19, 50–88.

Walther, J. B. & D’Addario, K. P. (2001). The impacts of emoticons on message interpretation in

computer-mediated communication. Social Science Computer Review, 19, 323–345.

Whitty, M. & Gavin, J. (2001). Age=sex=location: Uncovering social cues in the development of

online relationships. CyberPsychology & Behavior, 4, 623–630.

Wildermuth, S. M. (2001). Love on the line: Participants’ descriptions of computer-mediated close

relationships. Communication Quarterly, 49, 89–95.

Wildermuth, S. M. (2004). The effects of stigmatizing discourse on the quality of on-line relation-

ships. CyberPsychology & Behavior, 7, 73–84.

Wright, K. B. (2000). Perceptions of on-line support providers: An examination of perceived

homophily, source credibility, communication and social support within on-line support

groups. Communication Quarterly, 48, 44–59.

Wright, K. B. (2004). On-line relational maintenance strategies and perceptions of partners within

exclusively internet-based and primarily internet-based relationships. Communication

Studies, 55, 239–253.

172 T. L. Anderson & T. M. Emmers-Sommer