Do love teams affect the ratings of Princess and I?

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Do love teams affect the ratings of Princess and I?

An analysis of national household ratings and love team screen times

MC*

January 2013

* An aspiring economist and a TV enthusiast. She holds a master’s degree in Economics and is currently

a graduate student of Mathematics. Questions and comments are most welcome at

[email protected]

I want to thank Christina for her technical assistance and valuable comments; Vanessa, Rachelle,

Marivic, Katherene, and Rosee for their assistance in data collection; and the KathQuenatics group fortheir support and encouragement. All errors and omissions are mine. Because speculative bias may arise

out of these affiliations, I have clearly laid out the methodology so that others may replicate my findings.

I understand that the burden of proof is on me, and hence have given utmost care to ensure fairness

and impartiality in this report. This is not meant to be published.

mailto:[email protected]





Do love teams affect the ratings of Princess and I?

An analysis of national household ratings and love team screen times

This is a simple statistical exercise that wishes to find out if love teams, or a particular love team in the

story, drove the ratings of Princess and I. Here are the salient points of the paper:

• Princess and I successfully maintained its number one ranking during episodes that resolved

plot points and added milestones to the love triangle issue. Hence, ratings would have been

preserved or raised higher by increasing the frequency of revelations or the turnover of

significant plot points that determined the course of the story.

• Ratings tended to rise with additional airtime between Jao and Mikay. Mere interaction

between these two characters induced additional viewership, and increased exposure for

the love team (for romantic developments or otherwise) would have boosted the show’s

performance. Since ratings represent general viewership, the findings suggest that they are

favored by the majority of the audience.

• The Mikay and Gino pairing did not affect the show’s ratings. Given this love team’spopularity, the findings suggest that they may be catering to certain demographics instead

of having a universal appeal.

This paper is not meant to influence who Mikay should end up with (i.e., the endgame), but merely to

illustrate that it is possible to determine the audience's response to specific elements of a TV series

through ratings analysis. In the case of a love triangle, ratings analysis can help the network properly

determine if the audience favors one love team over another. Hence, the creators of a show can

properly respond to audience demand and maintain or even raise the show's ratings accordingly.



I. Introduction

Princess and I is the tale of Mikay, the long lost Princess and heir to the throne of Yangdon. She was

taken to the Philippines after Ashi Behati’s failed murder attempt and grew up as an adopted child in a

poor Filipino household. The story chronicles her struggles fitting into her adoptive family, and

sustaining her education through work and scholarship. Midway through the story, King Anand, her true

father, and Ashi Behati, separately found out that the princess is alive, and “Book 1” culminates with the

search for the princess and the revelation of her true identity. “Book 2” reveals the East-West conflict

and Ashi Behati as the true blood-heir to the throne of Yangdon, which explains her association with the

rebels and attempts to overthrow the current monarch. She and her son Dasho Jao were sent to exile

after their true identities were exposed. Ashi Behati manipulated Dasho Jao to believe that she has been

killed, fuelling his anger at the kingdom with her loss. He joins the rebellion after losing hope of any

reconciliation with Mikay, his former fiancée. Ashi Behati and the Eastern faction then take over the

palace and imprison King Anand. One week remains before series ends.

Mikay’s love interests have also played a second but persistent layer in the story, which ignited much

speculation about who she will end up with (i.e., the endgame). The series started with three

competing men: Kiko, her best friend; Gino, a bad boy in school; and Dasho Jao, a prince from Yangdon

and son of Ashi Behati. Kiko was eliminated early in the competition, reducing the love square into a

triangle. It is now a toss between her first and now forbidden love (Dasho Jao), and her current fiancé

whom she promised to love in due time (Gino). It appears that the love triangle will only reach its

resolution when the series ends this February.

Inevitably, the love triangle spurred competition between two fan bases (Team Jao vs. Team Gino),

both of which assert that they hold majority of the show’s viewers. This seeming urgency to prove

their respective numbers stems from earlier promotional interviews, where cast members said the show

will support the love team most favored by the majority. Gino supporters, in particular, can be seen

trending on Twitter almost every night, and have shown considerable attendance in the first two

basketball games promoting the series. On the other hand, those in favor of Jao claim to possess a wider

demographic, consisting mostly of the adult/working population who would not spend time ensuring

their preferred love team trends on Twitter, nor attend the basketball games, but nonetheless continue

to support the show.

Interestingly, one of the criticisms about Princess and I is its tendency to focus on the love triangle

instead of the plot.1 Enrique Gil, who plays Dasho Jao, has cited in a number of interviews that both love

teams get their fair share of airtime, that Mikay “bounces” from Gino to Jao and back again every few

weeks to cater to both fan bases.2

In contrast, plot-related developments progress at a much slower

pace, with Mikay’s identity revealed five months after the series began, and with most of December

transpiring with barely any reference to the East-West conflict.

1Based on posts in the Princess and I Royal Forum, Pinoy Exchange threads, and comments on Bais (2013).

2For example, see R. Siazon (2012).



But do love teams have an impact on the show’s ratings? From a business standpoint, love team

exposure is a sound strategy if they bring up the ratings, considering that ratings remain one of the best

indicators of general viewership. Moreover, while differences in advertisement pricing rest mainly on

target demographics, ratings serve as a baseline for which advertisers consider a show’s ability to

generate sales. Considering the intensity of fan wars generated by the show, one would think that the

weight of the show’s popularity rests on the love triangle instead of the plot. However, this “noise”

comes mostly from online sources, which hardly represent general viewership considering that only 30%

of Filipinos have Internet access3, and only about 9.5 million Filipinos are on Twitter

4.

Through regression analysis, this study establishes a relationship between the show’s ratings and each

love team’s screen time. The model uses seasonally-adjusted ratings as dependent variable, and love

team screen times as explanatory variables, where screen time is measured as the number of seconds

that each love team interacts in an episode. Seasonally-adjusted ratings for Walang Hanggan and Ina,

Kapatid, Anak are used to control for co-movement of primetime ratings and other factors that affect

general viewership for each night. Two counterfactual tests are also used to confirm the regression

results. The study uses 119 observations during the period of 16 April – 31 December 2012.

The study finds that general viewership for Princess and I rises with an increase in the screen time of

Jao and Mikay’s love team. Particularly, an additional minute of screen time increases ratings by 0.1 to

0.3 percentage points. On the other hand, ratings are not affected by the length of time of Mikay and

Gino’s screen time, as the estimates are far from being significantly different from zero. Counterfactual

tests suggest that not only do general viewers prefer the Jao-Mikay love team, but there is some level of

aversion towards the Mikay-Gino tandem. Discussion of possible reasons and implications follow.

The paper flows as follows: We begin with an analysis of the behavior of Princess and I ratings based on

Kantar Media/TNS data (Part II). This section also examines what makes Princess and I number one, and

establishes the motivation behind the regression model. We discuss data definitions and model

specification Part III, and interpret the results in Part IV. In Part V, we conclude and cite some areas for

further research. The review of literature and diagnostic checks are not included here for purposes of

brevity, and can be made available upon request.

II. Initial Impressions of the Ratings Data

The study makes use of Kantar Media/TNS ratings data for three reasons: First, it has a larger sample

and a nationwide scope, in contrast with AGB Nielsen which only samples Metro Manila households.

Second, it is commonly cited by ABS-CBN through its news, which eliminates any downward bias in

terms of network preferences. Third, Princess and I consistently ranks number one or two under this

3The State of Broadband 2012

4Semiocast.com



survey’s primetime category, in contrast with AGB Nielsen where the show usually ranks between third

and sixth place. Consistency in terms of ranking permits richer data analysis when the ratings are

compared with competing primetime shows.

In 2012, Princess and I’s ratings generally performed better than the series average from June until 25

October, after which ratings consistently declined. [Figure 1—Total Household Ratings for Princess and

I] After 25 October, even the best-performing episodes were marginally higher than the series average.

Low ratings were evident during religious and traditional holidays, with some of the lowest-rating

episodes including All Saints’ Day, Halloween, Christmas, Christmas Eve, and New Year’s Eve. The ratings

for the show were also relatively low during the beginning, as the series was gaining momentum and

gathering the general viewers' interest.

The ratings of Princess and I; Walang Hanggan; and Ina, Kapatid, Anak follow the same trend,

although the direction of causality is unclear. [Figure 2—Total Philippine Household Ratings for Princess

and I; Walang Hanggan; and Ina, Kapatid, Anak] This is understandable considering that they sit next to

each other’s time slots, which raises the probability of viewer spillovers from one show to the other. It is

highly likely that Walang Hanggan (WH) pulled up Princess and I’s (PAI) ratings in the course of its run,

considering it was already a top-rating show when the latter premiered in April. This can explain PAI’s

robust performance before October, and the sudden, seemingly irrecoverable drop after WH ended. In

contrast, PAI and Ina, Kapatid, Anak (IKA) dawdle between first and second place in primetime rankings,

making it difficult to establish which show gains more interest and influences the other’s ratings. At

best, the figures after WH ended reflect the PAI’s true ratings as a standalone show.

What makes PAI number 1? Figure 3 [Difference between the Ratings of PAI and Top-rating Shows]

demonstrates that the ratings with largest discrepancy between WH and IKA happened mostly during

episodes that address or resolve events related to the show’s main plot. Notably, PAI maintained its lead

against WH in September, when the episodes were closing in on the revelation that Mikay is the lost

princess of Yangdon. In contrast, PAI gained its largest leads against IKA during the royal engagement, in

which Yin publicly announced Ashi Behati’s betrayal; and at point where Mikay found the East’s

medallion under Ashi Behati’s bed. There are love-team related episodes that also garnered high

margins, but these were not leaning towards a particular love team but more on who Mikay will choose

or end up with. [Table 1 - Top ten episodes with the largest ratings against Walang Hanggan or Ina,

Kapatid, Anak ]

These charts show that Princess and I can maintain its ranking, and perhaps even up its rating, if it

hastens the pace of its storytelling. Figure 3 suggests that Princess and I retained its successive lead on

episodes that resolved plot points and added milestones to the love team issue. Hence, one way to

preserve or raise the ratings is to the increase the frequency of revelations or turnover of significant plot

points that determine the course of the story. However, plot aside, it remains unclear if it the love team

issue is of secondary or primary importance to the show’s popularity. This is what the study aims to find

out in the following section.



20%

25%

30%

35%

40%

45%

16-Apr 16-May 16-Jun 16-Jul 16-Aug 16-Sep 16-Oct 16-Nov 16-Dec

PAI Series Average Poly. (PAI)Gaps denote unavailable data.Source: Kantar Media/TNS.

31-Dec

Figure 1. Total Household Ratings for Princess and I

Trend

20%

25%

30%

35%

40%

45%

50%


PAI WH IKA

PAI = Princess and I; WH = Walang Hanggan; IKA = Ina, Kapatid, Anak.Gaps denote unavailable data.Source: Kantar Media/TNS.

31-Dec

Figure 2. Total Philippine Household Ratings forPrincess and I; Walang Hanggan; and Ina, Kapatid, Anak



Table 1. Top ten episodes with the largest lead in ratings

against Walang Hanggan or Ina, Kapatid, Anak

Date Lead Against Competing Show (%)04-Sep 2.7

18-Sep 2.7

04-Dec 2.7

21-Nov 2.6

19-Sep 2.4

27-Nov 2.4

10-Sep 2.1

01-Oct 2.1

24-Sep 2.0

03-Oct 2.0

-0.1

-0.05

0

0.05


Figure 3. Difference between the ratings of PAIand top-rating shows* (percentage points)

vs. Walang Hanggan vs. Ina, Kapatid, Anak

* Computed as Rating(PAI) - Rating(top-rating show). Positive values denote superiority over saidshows (and PAI is number 1). Estimates for IKA were omitted for 26 Oct and days prior, where PAIwas consistently higher but remained second to WH. Gaps denote unavailable data.Source: Kantar Media/TNS data.

Oct-26:WalangHangga

Sep-04: Behati finds out that Mikayowns the handkerchief. Esmeraldafinds out that Mikay is the lost

princess.

Sep-18: Anand finds outthat Mikay is the lostprincess. Mikay spillscoffee on Behati's shoe.

Nov-21: Final legof the dashocompetition. Jaowins.

Dec-04: Royalengagement. Yinannounces Behati'sbetrayal.

Nov-27: Mikaysees theSilanganmedallion under Behati'smattress.

31-Dec



III. Methodology and Data

The study uses love team screen times to determine their relative importance in ratings. Screen time

provides an objective measure for the appeal of a love team, considering the difficulty of quantifying

such without bias. In this study, screen times are measured for scenes where a love team interacts,

whether as part of the current plot’s timeline or as a flash back. Interaction is qualified as direct

conversations, physical interaction, and physical awareness of each member of the love team. Hence,

one-way conversations, scenes where one is thinking of the other, and similar situations are excluded

from this measure. The stringent requirement rests on the assumption that viewers wish to see the

couple together, for whatever context their fictional relationship is in. At the same time, the interaction

requirement reduces the possibility that the impact of the love team is dampened by the context of the

scene being measured. Hence, while somewhat limited, screen times provide a measure of the lower

limit of a love team’s desirability.

Data collection: Screen time data is collected by counting the number of seconds of a scene where a

love team interacts. Seconds are counted for both love teams in case all three members of the love

triangle appear in a scene. Data for each episode is gathered through videos uploaded in TFC.tv and

iwantv.com.ph. On the other hand, Kantar Media/TNS ratings data are gathered from Pep.ph and the

Kantar Media/TNS Facebook Page.

The study uses ordinary least squares to measure the relationship between ratings and screen time.

Ordinary least squares (popularly called OLS) is a standard statistical technique for estimating the

relationship of parameters in a linear regression model. The linear regression model in this study

consists of the rating as dependent variable, and each love team’s screen times as explanatory variables.

The ratings are seasonally adjusted using the Hodrick-Prescott filter to account for possible changes in

viewing habits for the months involved in the sample. The combined ratings of Walang HangganWH and

Ina, Kapatid, Anak IKA are used as a control variable to capture causality, seasonality (including holidays)

and other factors that might influence viewership for a particular episode. In this variable, the ratings of

Walang HangganWH are used for 16 April to 26 October, while the ratings of Ina, Kapatid, Anak IKA are

used for 29 October to 31 December. Because the direction of causality is hard to establish, it is not

meant to be interpreted but to provide a base case for which other variables, such as love team screen

times, may be added. The regression equation can be formally represented as follows:

Where RATING = seasonally adjusted ratings of Princess and I

JMTIMING = length of scene involving an interaction between Jao and Mikay

MGTIMING = length of scene involving an interaction between Mikay and Gino

WHIKA = seasonally adjusted ratings of Walang Hanggan and Ina, Kapatid, Anak



The study uses a sample of 119 Princess and I episodes through April 16 – December 31, 2012. [Table 2

– Summary Statistics] After seasonal adjustment, the average rating for the show is 34.3%, with a

minimum of 29.1% and a maximum of 37.1%. These estimates are very close to the parameters of the

merged WH and IKA ratings, sensibly since as illustrated these shows exhibit co-movement. Note that

minimum screen time for either love team is zero, suggesting that there were episodes where one love

team did not have any form of interaction at all. In contrast, there were episodes where either love

team had an interaction of more or less 12 minutes, or about 60% of a 20-minute episode’s run time.

The screen time averages and standard deviations are also relatively close, lending credence to the claim

that each love team is given fair exposure.

Simple correlations show that Princess and I’s ratings rise with an increase in Jao and Mikay’s screen

time. [Table 3 – Correlation Matrix] The correlation is positive at 32.6%. On the other hand, there is a

very weak but negative relationship between the ratings and Mikay and Gino’s airtime (-2.6%). As

expected, the merged ratings of WH and IKA are strongly correlated with those of PAI. The correlation

matrix is not conclusive as it only estimates pairwise relationships, but provides a good preview of the

relationship we might expect between PAI’s ratings and each independent variable in the regression

analysis.

Table 2. Summary Statistics

Variable Description Obs Mean Std. Dev. Min Max

RATING National household ratings,

seasonally adjusted

119 0.3434 0.0242 0.2914 0.3712

WHIKA Merged ratings of Walang

Hanggan and Ina, Kapatid, Anak ,

seasonally adjusted

119 0.3628 0.0364 0.2909 0.4061

JMTIMING Screen time of Jao and Mikay love

team, in seconds

119 156.3109 168.1357 0 722

MGTIMING Screen time of Mikay and Gino

love team, in seconds

119 148.8319 151.6666 0 701

Table 3. Correlation Matrix

RATING WHIKA JMTIMING MGTIMING

RATING 1

WHIKA 0.8496 1

JMTIMING 0.3261 0.2703 1MGTIMING -0.0259 0.0192 -0.1369 1



IV. The Contribution of Love Team Screen Time to Princess and I’s Ratings: Results and

Discussion

Results show that greater exposure for the Jao and Mikay pairing raises the show’s ratings. An

additional second of Jao and Mikay (JaoMik) screen time raises the show’s ratings by 0.001 percentage

points (pps). [Table 4 – Regression Results] This means that an additional minute of a JaoMik sequence

raises the rating of Princess and I by 0.1 pps, while a five-minute sequence can increase the show’s

ratings by 0.3 pps. The coefficient estimate is significant at the 10% level. An alternative specification

using the logarithmic form of each love team’s screen time strengthens the result for the JaoMik pairing.

Using this specification, a 1% increase in JaoMik screen time raises the show’s rating by 0.3 pps. For

example, given that the mean screen time for the pairing is 156 seconds, or about 2.6 minutes,

increasing the tandem’s screen time to five minutes will increase the show’s rating by 0.6 pps. In this

model, the estimate is significant at the 1% level, a stronger result.

Meanwhile, the Mikay-Gino pairing does not have any apparent implication on the show’s ratings.

For both specifications, the coefficient estimates for the Mikay-Gino (MiGi) screen time generated p-

values higher than the 10% significance level, suggesting that they are not statistically different from

zero.

Table 4. Regression Results

Variable Description Model 1:

Screen Time in

Seconds

Model 2:

Log of Screen

Time in Seconds

WHIKA Merged ratings of Walang

Hanggan and Ina, Kapatid, Anak ,seasonally adjusted

0.5465

(0.00)

0.5469

(0.00)

JMTIMING Screen time of Jao and Mikay


1.44E-05

(0.05)

0.0033

(0.01)

MGTIMING Screen time of Mikay and Gino


-4.47E-06

(0.57)

-0.0016

(0.20)

CONSTANT 0.1435

(0.00)

0.1421

(0.00)

R-SQUARED 0.73 0.74

Parentheses denote p-values.

A counterfactual test confirms the JaoMik result and shows that MiGi exposure actually decreases

ratings. [Table 5 – Counterfactual Tests] The counterfactual test involves measuring the effect on the

ratings of the absence of a love team in an episode (i.e., 1 = there is no love team interaction during the

episode, 0 otherwise). This test provides a baseline case to confirm the results in case of measurement

error. Interestingly, the results show that the absence of JaoMik interaction in an episode decreases the

rating by 0.7 pps, while the absence of MiGi interaction actually increases the rating by 0.6 pps.



Conversely, these results suggest that the mere presence of the JaoMik tandem raises the ratings, while

the presence of the MiGi pairing decreases the ratings. These estimates are significantly different from

zero at the 5% level.

A second counterfactual test confirms that general viewers prefer more airtime for the JaoMik pairing

than for the MiGi couple. Measured as the difference between the screen times of JaoMik and MiGi,

the variable TIMEDIFF measures how much viewers favor additional screen time for the JaoMik

partnership compared to the MiGi pairing. The regression results show that that an additional second of

time difference increases the rating by 0.001 pps, or equivalent to an additional 0.29 pps for a five

minute difference in screen times. The estimate is significantly different from zero at the 5% level.

Table 5. Counterfactual Tests

Variable Description Counterfactual Test 1:

Absence of Love

Team in an Episode

Counterfactual Test 2:

Difference in JM and

MG Timings

WHIKA Merged ratings of WalangHanggan and Ina, Kapatid,

Anak , seasonally adjusted

0.5566(0.00)

0.5528(0.00)

NOJM Absence of JaoMik

interaction

-0.0068

(0.02)

NOMG Absence of MiGi

interaction

0.0057

(0.04)

TIMEDIFF JMTIMING – MGTIMING, in

seconds

9.70E-06

(0.05)

CONSTANT 0.1416

(0.00)

0.1428

(0.00)

R-SQUARED 0.75 0.73

These results beg the question: Why do general viewers positively respond to the JaoMik love team?

The author offers three possible explanations: First, departing from the love team issue, it is evident

that the JaoMik story is closely tied to the main plot a) because of Jao’s relationship with main

antagonist, Ashi Behati; b) because Jao used to be the competing heir to the throne; and c) because

later in the series, he is revealed to be the lost prince and future leader of the East. Hence, it is natural

for viewers to seek scenes with interactions between Jao and Mikay, since they are also involved in the

movement of the main plot. Second, viewers may be responding based on their understanding that the

JaoMik tandem is the main pairing in the show, evidenced by Enrique Gil and Kathryn Bernardo’s castingas lead man and woman, respectively; promotional photos; and suggestions of mutual attraction very

early in the series. If the ratings are based on expectations, then viewership rises during episodes with

more interactions between Jao and Mikay because the audience anticipates that they will eventually

end up together. Alternatively, there may be loss of viewership during episodes with “less relevant”

pairings if casual viewers are merely interested in the “meat” of the story. Third, and equally plausible,



simply boils down to preference: that general viewers like the JaoMik story, the chemistry between the

actors that play the roles, and/or the actors’ appeal or acting capability.

But perhaps the more compelling question is this: how come general viewers seemingly show

indifference (or even aversion) towards the MiGi tandem? The result comes as a surprise considering

ABS-CBN’s strategy of promoting this particular love team, the budding romance between Kathryn

Bernardo and Daniel Padilla, and Daniel Padilla’s immense popularity especially among teenage girls.

Oddly, these personality-related factors are not sufficient in influencing the ratings of Princess and I. And

if viewers look for more than real-life elements in watching a show, then it is possible that the MiGi

partnership does not warrant additional viewership a) because the audience finds their story less

persuasive; and/or b) if it boils down to preference, then they do not diffuse enough appeal that would

engender a response from the general audience, either because of their chemistry, acting ability, and/or

the personality of the actors who play the roles.

This is not to say that the Kathryn Bernardo-Daniel Padilla love team is worthless. In fact, they are

considered to be one of the most successful love teams of 2012, generating a huge following collectively

called KathNiels, with celebrity shows and magazines following the progress of their relationship. They

starred as a pair in two movies in 2012, one of which earned more than P300 million in the box office,

and will be shooting a new movie and a TV show in 2013. The ABS-CBN network sees their potential, and

that by itself should be considered a measure of success.

It is possible that the MiGi love team caters to specific demographics, instead of having a universal

appeal. This is because the MiGi love team remains popular whether or not the general audience

agrees. This may have bidden well for better-targeted advertisements if the network chose to take

advantage of the phenomenon; and in future Kathryn Bernardo-Daniel Padilla projects, the network may

even command higher prices as the pair’s market value increases.

On the other hand, it would have made sense for the show’s creators to extend the airtime for the

JaoMik tandem. Mere interaction between these two characters induces additional viewership, and

increased exposure for the love team (for romantic developments or otherwise) would have boosted

the show’s performance. Moreover, the show discouraged significant viewership in episodes where Jao

and Mikay had less or no interaction, audiences which may have represented specific demographics that

by consequence, the network failed to pursue.

V. Conclusion

What is the point? The show is ending in a few days, and the findings in this paper may be considered

moot and academic. However, the underlying implications remain important in the creation of

succeeding shows, particularly those involving love triangles. First, as in any love triangle debate, avid

viewers tend to self-select towards a specific love team, and it is possible to ascertain the viewer’s

preferred pairing not just through online polls or promotional events but also through this type of



statistical analysis. Online polls and promotional events, by their very nature, tend to disregard certain

demographics because of their inability to capture universal interest and participation. In contrast,

ratings analysis sheds light on the pairing that is most favored and can help the network properly

determine which one is preferred by the general audience. Because ratings represent general

viewership, the findings of the study suggest that the majority is in favor of the Jao and Mikay pairing.

Second, competing love teams may contribute to the ratings but they cannot singlehandedly account for

the show’s success. Viewers are discerning and look for more than personalities or behind-the-scenes

chismis in watching a show. There are unquantifiable factors that come into play, such as tight

storytelling, a compelling plot, an emotional tug, mood, setting, and other elements that entice people

not only to see the pilot but to consistently watch the series.

This study is far from all-encompassing and the current model can be enhanced to better explain the

significance of the love teams. First, indicators that represent the plot of the story may be added to

verify the findings and confirm if the ratings are primarily driven by the storytelling. One can consider

measuring Ashi Behati’s screen time since she is the main antagonist of the show. Second, milestones

relating to each love team may also be included to add some weight into the love team angle. Lastly, the

very notion of screen time can be redefined so as to include not just mere interaction but also moments

relating to the love team, including reminiscing scenes, thoughts about each other, and one-way

conversations. This will add noise to the estimation but may also help refine the current results.

References:

Bais, Andy. Has ‘Princess’ lost its focus? January 11, 2013. http://entertainment.inquirer.net/75981/has-princess-lost-its-focus (accessed January 11, 2013).

James G. Webster, Patricia F. Phalen, Lawrence W. Lichty. Ratings analysis: The theory and practice of

audience research. New Jersey: Lawrence Erlbaum Associates, 2006.

Siazon, Rachelle. "Enrique Gil is happy that his team-up with Kathryn Bernardo is being given fair

exposure." Push. November 29, 2012. http://www.push.com.ph/features/8703/enrique-gil-is-

happy-that-his-team-up-with-kathryn-bernardo-is-being-given-fair-exposure/ (accessed January

11, 2013).

"The State of Broadband 2012: Achieving Digital Inclusion For All." Broadband Commission for Digital Development. September 2012. http://www.broadbandcommission.org/Documents/bb-

annualreport2012.pdf (accessed January 11, 2013).

Traudt, Paul J. Media, Audiences, Effects: An Introduction to the Study of Media Content and Audience

Analysis. Boston: Pearson/Allyn and Bacon, 2005.

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