Linguistic profiles on microblogging platforms to characterize political leaders: The Ecuadorian case on Twitter

Social interaction on microblogging platforms is becoming a reliable instrument for studying political communication characteristics. Microblogging platforms, such as Twitter, let citizens to engage in the political debate generating well-defined profiles in the platform. Using publicly available tweets it is possible to build a linguistic profile to compare leaders and average citizens. We describe the linguistic analysis of 330,000 tweets collected from 221 Ecuadorian tweeters classified into three different profiles: political leaders, leaders' followers, and average local users. We build a feature vector for each user's tweets using 12 psychological dimensions included in the LIWC (Linguistic Inquiry Word Count) text analysis software and compare users with different profiles using those vectors. Our findings show that the leaders group exhibits a different linguistic profile from the others two groups: around 30% of leader followers are similar to at least one leader while just 19% of average local users are similar to at least one leader. Furthermore, the results of our analysis allows to determine whether local users have some similar characteristics of language uses on social networks of political leaders' followers without relying on critical discourse analysis.

[1]  Ryan L. Boyd,et al.  The Development and Psychometric Properties of LIWC2015 , 2015 .

[2]  R. Zamora-Medina,et al.  Campaigning on Twitter: Towards the “Personal Style” Campaign to Activate the Political Engagement During the 2011 Spanish General Elections , 2014 .

[3]  Amit Srivastava,et al.  Leveraging candidate popularity on Twitter to predict election outcome , 2013, SNAKDD '13.

[4]  Stefan Kaufmann,et al.  Classifying Party Affiliation from Political Speech , 2008 .

[5]  John H. Parmelee,et al.  Politics and the Twitter Revolution: How Tweets Influence the Relationship between Political Leaders and the Public , 2011 .

[6]  Matthew Purver,et al.  Twitter Language Use Reflects Psychological Differences between Democrats and Republicans , 2015, PloS one.

[7]  Florencia Claes,et al.  Predicción de tendencia política por Twitter: Elecciones Andaluzas 2012 , 2013 .

[8]  Carmen Vaca,et al.  Geo-localized social media data to improve characterization of international travelers , 2016, 2016 Third International Conference on eDemocracy & eGovernment (ICEDEG).

[9]  David A. Huffaker,et al.  Dimensions of leadership and social influence in online communities , 2010 .

[10]  Francisco Segado-Boj,et al.  Líderes latinoamericanos en Twitter. Viejas costumbres para nuevos medios en tiempos de crisis políticas , 2015 .

[11]  Karolin Kappler,et al.  Communication dynamics in twitter during political campaigns: The case of the 2011 Spanish national election , 2013 .

[12]  Harald Schoen,et al.  Small worlds with a difference: new gatekeepers and the filtering of political information on Twitter , 2011, WebSci '11.

[13]  Maurice Vergeer,et al.  Campaigning on Twitter: Microblogging and Online Social Networking as Campaign Tools in the 2010 General Elections in the Netherlands , 2013, J. Comput. Mediat. Commun..

[14]  Scott Counts,et al.  Identifying topical authorities in microblogs , 2011, WSDM '11.

[15]  Isabell M. Welpe,et al.  Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment , 2010, ICWSM.

[16]  J. Pennebaker,et al.  The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods , 2010 .

[17]  Gregory J. Park,et al.  Automatic personality assessment through social media language. , 2015, Journal of personality and social psychology.

[18]  Rocío Zamora Medina,et al.  Campaigning on Twitter: Towards the "Personal Style" Campaign to Activate the Political Engagement During the 2011 Spanish General Elections , 2014 .

[19]  James P. Bagrow,et al.  Human language reveals a universal positivity bias , 2014, Proceedings of the National Academy of Sciences.

[20]  João Canavilhas,et al.  Jornalismo para plataformas móveis de 2008 a 2011: da autonomia à emancipação , 2011 .

[23]  Mary Beth Rosson,et al.  How and why people Twitter: the role that micro-blogging plays in informal communication at work , 2009, GROUP.

[24]  Munazza Ishtiaq.  Analysis of Twitter Data Using Sentiment Influencers , 2015 .

[25]  Daniele Quercia,et al.  In the Mood for Being Influential on Twitter , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

[26]  J. Bono,et al.  Charisma, positive emotions and mood contagion , 2006 .

[27]  Paul M. Haridakis,et al.  The 2008 Presidential Campaign: Political Cynicism in the Age of Facebook, MySpace, and YouTube , 2010 .

[28]  Susan T. Dumais,et al.  Mark my words!: linguistic style accommodation in social media , 2011, WWW.

[29]  Hongchul Lee,et al.  Sentiment analysis of twitter audiences: Measuring the positive or negative influence of popular twitterers , 2012, J. Assoc. Inf. Sci. Technol..

[30]  O novo ecossistema mediático , 2011 .

[31]  Masahiro Yamamoto,et al.  Did Social Media Really Matter? College Students' Use of Online Media and Political Decision Making in the 2008 Election , 2010 .

[32]  Stefan Stieglitz,et al.  Political Communication and Influence through Microblogging--An Empirical Analysis of Sentiment in Twitter Messages and Retweet Behavior , 2012, 2012 45th Hawaii International Conference on System Sciences.

[33]  S. Brownlow,et al.  Differential Forms Linguistic Content of Various of Political Advertising , 2000 .