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

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

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

    • “The evolution of social media intoa robust mechanism for socialtransformation is already visible.Despite many adamant critics whoinsist that tools like Facebook,Twitter, and YouTube are littlemore than faddish distractionsuseful only to exchange trivialinformation, these critics are beingproven wrong time and again.” Simon Mainwairing
    • The meteoric growth of social media Source: PEW Internet & American Life Project, 2012
    • The meteoric growth of social media Source: PEW Internet & American Life Project, 2012
    • 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
    • Challenges and opportunities of social media research• 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
    • Challenges and opportunities of social media research• 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
    • Challenges and opportunities of social media research• 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. Sources; Krishnamurthy and Wills, 2009; Small, 2011; Fitton, Gruen et al., 2009
    • 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
    • Case study: #teaparty• 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
    • Case study: #teaparty Monthly volume of #teaparty tweets (per number of tweets)300,000 275,408250,000200,000 181,122150,000 156,680 204,575 198,596 47,787100,000 129,215 174,582 68,204 50,000 51,197 60,405 50,349 0 33,700 42,357 3,113 11,391 Source: Raynauld, 2013
    • Case study: #teaparty Monthly number of unique twitterers who contributed at least once to the #teaparty conversation (per number of twitterers20,00018,00016,00014,000 12,000 10,000 8,000 6,000 4,000 2,000 0 Source: Raynauld, 2013
    • Case study: #teaparty• 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. Source: Raynauld, 2013
    • Case study: #teaparty Network analysis December 14, 2009 to December 20, 2009 Number of 877 @replies Number of nodes 654 Number of edges 648 Average degree 0.991 Source: Raynauld, 2013
    • Case study: #teaparty Network analysis November 1, 2010 to November 7, 2010 Number of 4,424 @replies Number of nodes 3,258 Number of edges 3,542 Average degree 1.087 Source: Raynauld, 2013
    • Case study: #teaparty Network analysis October 25, 2010 to October 31, 2010 Number of 4,280 @replies Number of nodes 2,630 Number of edges 3,131 Average degree 1.19 Source: Raynauld, 2013
    • Case study: #teaparty Network analysis January 10, 2011 to January 16, 2011 Number of 688 @replies Number of nodes 807 Number of edges 624 Average degree 0.773 Source: Raynauld, 2013
    • Case study: #teaparty• 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- #teaparty 6- #tlot 2- #tcot 7- #ocra 3- #p2 8- #912 4- #sgp 9- #twisters 5- #gop 10- #iamthemob Source: Raynauld, 2013
    • 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.
    • QUESTIONS orCOMMENTS