PRLN210 - #SOCIALMEDIARESEARCH: Basic principles and quasi-endless possibilities

“The evolution of social media into a robust mechanism for social transformation is already visible. Despite many adamant critics who insist that tools like Facebook, Twitter, and YouTube are little more than faddish distractions useful only to exchange trivial information, these critics are being proven wrong time and again.”

Simon Mainwairing

The meteoric growth of social media

Source: PEW Internet & American Life Project, 2012

Source: PEW Internet & American Life Project, 2012

The meteoric growthof social media

Why study social media?

• Impact of Web 2.0 media tools on different fields of activity:

• Political communication;• 2006: 16% of major party congressional

contenders on Facebook (U.S. Midterm elections);

• 2008: 79% of major party House hopefuls on Facebook (U.S. Presidential elections);

• 2010: 82% of major party congressional candidates on Facebook before elections (U.S. Midterm elections).

• Advertising;• Online dating (e.g.: “Spotted at” pages on

Facebook);• Journalism;• Etc.Sources; Williams and Gulati, 2009; Johnson and Perlmutter, 2009; Lariscy, Avery et al., 2009; Wiilliams and Gulati, 2011;

Why study social media?

• The impact of Web 2.0 media tools on public relations:• Social media as moved from “from ‘buzz word’

status to strategic tool” for PR specialists;• Results from a survey of 273 U.S.-based PR

practitioners in 2011:• Between 0 and 35 years of experience;• Between 21 and 61 years-old (median age: 40);• 35 per cent reported using Twitter in the 15

mins before taking the survey;• 51.2 per cent reported using Twitter in the

hour before taking the survey;• 90 per cent reported using Twitter in the 24-

hour window before taking the survey.

Sources; Sweetser and Kelleher, 2011; Eyrich, Padman et al.,2008

Challenges and opportunities of social media research

• What is the research question?• Identification of one or multiple research problems;• Ethical considerations;• Importance to have a basic understanding of social

media (in other words, play with these tools!):• Structure;• Functionalities;• Etc.

• What are the research objectives?• Identification of one of multiple research hypotheses:

• Can it be done?• Can it be verified?• Can it be replicated?• Etc.

• Identify limitations.Source: Raynauld, Giasson et al., 2011


• Adapting your approach (flexibility):• Two main functions: (1) content dispersion and

(2) social interaction;• Social networking services share three broad

traits:• Users can create and manage profile pages

within the confines of an established system;• Users can display their connections with other

users within the established system;• Users can access and browse through “their list

of connections and those made by others” within the established system.

• They all have distinct properties (e.g.: “like” function on Facebook;

• Constantly-evolving nature of social media channels. Sources; Boyd and Ellison, 2007; Papacharissi and Gibson, 2011


• Data mining and archiving (sampling):• Selection of a sampling tactic (in the case of Twitter):

• Monitoring accounts;• Monitoring tweets:

• Keywords;• Social interaction mechanisms (e.g.:

@retweets, @mentions, etc.);• Hashtags;• Hyperlinks;• Etc.

• Data mining and analysis technology;• Hardware;• Software (importance of open-source tools).

• Flexibility now “the name of the game”.

Sources; Raynauld, Giasson et al., 2011; Hemphill, Shapiro et al., 2012; Zappavigna, 2011; Mascaro, Black et al., 2012


Sources; Krishnamurthy and Wills, 2009; Small, 2011; Fitton, Gruen et al., 2009

• Selection of an analytical approach (in the case of Twitter):

• Users:• Presence of “personally identifiable

information” (PII);• Verifiability of information provided.

• Digital material:• Text (140 characters);• Hyperlinks (often shortened);• Multimedia (e.g.: twitpic, instagram, keek,

etc.);• Etc.

• Concerns with interpretation:• Classifying content by associating it to specific

issues, events, etc.;• Coordinating decentralized conversation;• Issuing comments or opinions.

Case study: #teaparty

• What is the Tea Party movement?• Mainstream emergence in February 2009;• Essentially leaderless;• Research hypotheses:

• Decentralized organizational structure;• Hyper-fragmented interests.

• Quantitative content analysis of #teaparty discourse on Twitter:

• Tweets with #teaparty hashtag posted between December 9, 2009 at 22h41 +0000 and March 19, 2011 at 15h40 +0000 (Midterm elections);

• Twapper Keeper for data mining and archiving (open-source);

• MySQL and Gephi (version 0.8.1 beta) for data analysis.

Sources; Raynauld, 2013


• Overview of the #teaparty tweeting dynamic:• 1,747,306 tweets with at least one #teaparty

hashtag;• 79,564 unique twitterers;• 96.64 per cent of the #teaparty tweets with all

the correct information (technical issue affecting 3.36% of the dataset).

Source: Raynauld, 2013


Decem

ber 2

009

Janu

ary 20

10

Febr

uary

2010

Marc

h 201

0

April

2010

May

2010

June

2010

July

2010

Augus

t 201

0

Sept

embe

r 201

0

Octobe

r 201

0

Novem

ber 2

010

Decem

ber 2

010

Janu

ary 20

11

Febr

uary

2011

Marc

h 201

1

0

50,000

100,000

150,000

200,000

250,000

300,000

51,197

68,204

60,405

47,787

50,349

156,680

129,215

174,582

181,122204,575

275,408

198,596

42,35733,700

3,113

11,391

Monthly volume of #teaparty tweets (per number of tweets)


December

2009

January

2010

Febru

ary 2010

March 2010

April 2010

May 2010

June 2010

July 2010

August

2010

Septem

ber 2010

October

2010

November

2010

December

2010

January

2011

Febru

ary 2011

March 2011

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

20,000

Monthly number of unique twitterers who contributed at least once to the #teaparty conversation (per number of twitterers




• 85,629 @replies (4.9% of the dataset) by 11,296 unique #teaparty twitterers;

• 578,939 #teaparty tweets (31.13% of the dataset) by 54,802 unique users served a retweeting function;

• 1,179,742 #teaparty tweets (67.52% of the dataset) by 54,534 unique authors featured at least one hyperlink.



Number of @replies

877

Number of nodes

654

Number of edges

648

Average degree 0.991

December 14, 2009 to

December 20, 2009

Case study: #teapartyNetwork analysis



Number of @replies

4,424

Number of nodes

3,258

Number of edges

3,542


November 1, 2010 to

November 7, 2010

Network analysis



Number of @replies

4,280

Number of nodes

2,630

Number of edges

3,131

Average degree 1.19

October 25, 2010 to October 31,

2010

Network analysis



Number of @replies

688

Number of nodes

807

Number of edges

624


January 10, 2011 to January 16,

2011

Network analysis



• 49,797 different hashtags (including the #teaparty hashtag) used by #teaparty twitterers;

• 1,747,306 #teaparty tweets with at least one hashtag;• 178,417 different hashtag combinations (hyper

fragmentation;• 10 most popular hashtags:

1- #teaparty2- #tcot3- #p2 4- #sgp5- #gop

6- #tlot 7- #ocra 8- #912 9- #twisters 10- #iamthemob

Conclusion

• Social media platforms are now an integral component of the modern media environment;

• Redefinition of traditional research approaches:• Mass media versus participatory media;• Top-down versus multidirectional information

flows and social interactions;• Constantly-evolving nature of social media (e.g.:

Facebook timeline);• Etc.

• The rise of “big data” research• Research shifting into a “perpetual beta” mode?• More “research on research” required.

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Date post:	28-Nov-2014
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PRLN210 - #SOCIALMEDIARESEARCH: Basic principles and quasi-endless possibilities

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