It’s All About Information? The Following Behaviour of Professors and PhD Students in Computer Science on Twitter

Stephanie Linek, Asmelash Teka Hadgu, Christian Pieter Hoffmann, Robert Jäschke, Cornelius Puschmann


In this paper we investigate the role of the academic status in the following behaviour of computer scientists on Twitter. Based on a uses and gratifications perspective, we focus on the activity of a Twitter account and the reciprocity of following relationships. We propose that the account activity addresses the users’ information motive only, whereas the user’s academic status relates to both the information motive and community development (as in peer networking or career planning).

Variables were extracted from Twitter user data. We applied a biographical approach to correctly identify the academic status (professor versus PhD student). We calculated a 2 × 2 MANOVA on the influence of the activity of the account and the academic status (on different groups of followers) to differentiate the influence of the information motive versus the motive for community development. Results suggest that for computer scientists Twitter is mainly an information network. However, we found significant effects in the sense of career planning, that is, the accounts of professors had even in the case of low activity a relatively high number of researcher followers – both PhD followers as well as professor followers. Additionally, there was also some weak evidence for community development gratifications in the sense of peer-networking of professors.

Overall, we conclude that the academic use of Twitter is not only about information, but also about career planning and networking.

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C. M. Anderson. (1997). Computer-mediated communication, the invisible college and visiting scholars: An exploratory study. J. Comput. High. Educ., 9(1), 27–48.

A. Bader, G. Fritz, & T. Gloning. (2012). Digitale Wissenschaftskommunikation 2010-2011 : Eine Online-Befragung. Gießener Elektronische Bibliothek, Gießen, p. 113.

C. L. Borgman. (2007). Scholarship in the digital age: Information, infrastructure, and the Internet. MIT Press, Cambridge, MA, p. 336.

M. Cha, H. Haddadi, B. Benevenuto, & P.K. Gummadi. (2010). Measuring user influence in Twitter: The million follower fallacy. In Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media, pp. 10–17, AAAI, Menlo Park, CA.

M. Cha, A. Mislove, & K.P. Gummadi. (2009) A measurement-driven analysis of information propagation in the Flickr social network. In Proceedings of the 18th International Conference on the World Wide Web, ACM, New York, NY.

V. Colson. (2011). Science blogs as competing channels for the dissemination of science news. Journalism, 12(7), 889–902.

J. Conway, & A. Rubin. (1991). Psychological predictors of television viewing motivation. Communication Research, 18 (4), 443–463.

C. Courtois, P. Mechant, L. De Marez, & G. Verleye. (2009). Gratifications and seeding behavior of online adolescents. Journal of Computer-Mediated Communication, 15, 109–137.

K. Crawford. (2009). Following you: Disciplines of listening in social media. Continuum, 23(4), 525–535.

T. Desai, A. Shariff, A. Shariff, M. Kats, X. Fang, & C. Christiano. (2012). Tweeting the meeting: An in-depth analysis of Twitter activity at Kidney Week 2011. PloS One, 7(7), e40253.

J. Dimmick, S. Kline, & L. Stafford. (2000). The gratification niches of personal e-mail and the telephone. Communications Research, 27 (1), 227–248

M. Ebner. (2009). Introducing Live Microblogging: How Single Presentations Can Be Enhanced by the Mass. Journal of Research in Innovative Teaching, 2(1), 91–98.

G. Eysenbach. (2011). Can tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact. Journal of Medical Internet Research, 13(4).

D. Ferguson, & E. Perse. (2000). The world wide web as a functional alternative to television. Journal of Broadcasting and Electronic Media, 44(2), 155–174.

A. Gruzd, & M. Goertzen. (2013). Wired academia: Why social science scholars are using social media. In Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 3332–3341.

A.T. Hadgu, & R. Jäschke. (2014). Identifying and analyzing researchers on Twitter. In Proceedings of the 2014 ACM Conference on Web Science, ACM, New York, NY, pp. 23–32.

F. Heider. (1958). The psychology of interpersonal relations. New York: Wiley.

J. Hopcroft, T. Lou, & . Tang. (2011). Who Will Follow You Back?: Reciprocal Relationship Prediction. In Proceedings of the 20th ACM International Conference on Information and Knowledge Management, ACM, New York, NY, pp. 1137–1146.

K.A. Karl, & J.V. Peluchette. (2011). „Friending“ professors, parents and bosses: A Facebook connection conundrum. Education for Business, 86, 214–222.

E. Katz, J. Blumler, & M. Gurevitch. (1974) Utilization of mass communication by the individual. In The uses of mass communications: Current perspectives on gratifications research, J. Blumler and E. Katz, Eds., Sage, Beverly Hills, CA, pp. 19–32.

S. Krishnamurthy, & W. Dou. (2008). Advertising with user-generated content: A framework and research agenda. Interactive Advertising, 8(2), 1–7.

R. Kumar, J. Novak, & A. Tomkins. (2006). Structure and evolution of online social networks. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, New York, NY.

H. Kwak, C. Lee, H. Park, & S. Moon. (2010). What is Twitter, a Social Network or a News Media? In Proceedings of the 19th International Conference on the World Wide Web, ACM, New York, NY, pp. 591–600.

H. Kwak, S. Moon, & W. Lee. (2012). More of a Receiver Than a Giver: Why Do People Unfollow in Twitter? In Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media, The AAAI Press, Dublin, pp. 499–502.

J. Letierce, A. Passant, J. Breslin, & S. Decker. (2010). Understanding how Twitter is used to widely spread scientific messages. Proceedings of the Web Science Conference.

M. Ley. (2009). DBLP: some lessons learned. Proc. VLDB Endow., 2(2), 1493–1500.

Y.-R. Lin, B. Keegan, D. Margolin, & D. Lazer. (2013). Rising tides or rising stars?: Dynamics of shared attention on Twitter during media events. CoRR, abs/1307.2785.

D. Lupton, “‘Feeling Better Connected’: Academics’ Use of Social Media,” Canberra, 2014.

A. Marwick, & D. Boyd. (2010). I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience. New Media & Society, 13(1), 114–133.

A. Mauranen. (2013).Hybridism, edutainment, and doubt: Science blogging finding its feet. Nord. J. English Stud., 12(1), 7–36.

B. Meeder, B. Karrer, A. Sayedi, R. Ravi, C. Borgs, & J. Chayes. (2011). We Know Who You Followed Last Summer: Inferring Social Link Creation Times in Twitter. In Proceedings of the 20th International Conference on World Wide Web, ACM, New York, NY, USA, pp. 517–526.

A. Mislove, S. Lehmann, Y.-Y. Ahn, J.-P. Onnela, & J.N. Rosenquist. (2011) Understanding the Demographics of Twitter Users. In Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, AAAI, pp. 554–557.

T. Mortensen, & J. Walker. (2002). Blogging thoughts: personal publication as an online research tool. In Researching ICTs in context, InterMedia, Oslo, pp. 249–279.

M. Nentwich & R. König. (2012). Cyberscience 2.0: Research in the age of digital social networks. Campus, Frankfurt am Main, p. 237.

M. Nielsen. (2011). Reinventing Discovery: The New Era of Networked Science. Princeton University Press, Princeton, NJ, p. 280.

N. Park, K. F. Kee, & S. Valenzuela. (2009). Being immersed in social networking environment: Facebook Groups, Uses and gratifications, and social outcomes. Cyberpsychology & Behavior, 12(6), 729–733.

J. Priem, & K. L. Costello. (2010). How and why scholars cite on Twitter. In Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem, Vol. 47, American Society for Information Science, Silver Springs, MD, USA, article 75.

J. Priem, & B. Hemminger. (2010). Scientometrics 2.0: New metrics of scholarly impact on the social web. First Monday, 15(7).

J. Priem, H.A. Piwowar, & B.M. Hemminger. (2012). Altmetrics in the wild: Using social media to explore scholarly impact. CoRR, cs.DL, 1203.4745.

R. Procter, R. Williams, J. Stewart, M. Poschen, H. Snee, A. Voss, & M. Asgari-Targhi. (2010). Adoption and use of Web 2.0 in scholarly communications. Philos. Trans. A. Math. Phys. Eng. Sci., 368(1926), 4039–4056.

D. Pscheida, S. Albrecht, S. Herbst, C. Minet, & T. Köhler. (2013). Nutzung von Social Media und onlinebasierten Anwendungen in der Wissenschaft. Dresden.

R. LaRose, D. Mastro, & M. Eastin. (2001). Understanding Internet usage: a social-cognitive approach to uses and gratifications. Social Science Computer Review, 19(4), 395–413.

C. Ross, M. Terras, C. Warwick, & A. Welsh. (2011) Enabled Backchannel: Conference Twitter Use by Digital Humanists. Documentation, 67(2),214–237.

T. Ruggiero. (2000). Uses and gratifications theory in 21th century. Mass Communication & Society, 3(1), 3–37.

G. Shao. (2009). Understanding the appeal of user-generated media: a uses and gratification perspective. Internet Research, 19, 7–25.

H. Shema, J. Bar-Ilan, & M. Thelwall. (2012) Research blogs and the discussion of scholarly information. PLoS One, 7(5), e35869.

N. Spinks, B. Wells, & M. Meche. (1999). Netiquette: a behavioral guide to electronic business communication. Corporate Communications, 4(3), 145–155.

T.F. Stafford, M. Stafford, & L.L. Schkade. (2004). Determining uses and gratifications for the internet. Decision Sciences, 35(2), 259–288.

J. Tang, T. Lou, & J. Kleinberg. (2012). Inferring social ties across heterogeneous networks. In Proceedings of the fifth ACM international conference on Web search and data mining. ACM, New York, NY, USA, 743–752.

J. Van Eck Paluchette, K. Karl, & J. Fertig. (2013). A Facebook „friend“ request from the boss: Too close for comfort? Business Horizons, 56, 291–300.

C. Wang, J. Han, Y. Jia, J. Tang, D. Zhang, Y. Yu, & J. Guo. (2010). Mining advisor-advisee relationships from research publication networks. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, New York, NY, USA, 203–212.

K. Weller, E. Dröge, & C. Puschmann (2011) Citation analysis in Twitter: Approaches for defining and measuring information flows within tweets during scientific conferences. In Proceedings of the ESWC 2011 Workshop on “Making Sense of Microposts”, pp. 1–12.

X. Wen, Y.-R. Lin, C. Trattner, & D. Parra. (2014(. Twitter in Academic Conferences: Usage, Networking and Participation over Time. In Proceedings of the 25th ACM Conference on Hypertext and Social Media. ACM, New York, NY, USA , pp. 285–290.

J. Zhang, C. Wang, & J. Wang. (2014). Who proposed the relationship?: recovering the hidden directions of undirected social networks. In Proceedings of the 23rd international conference on World wide web. ACM, New York, NY, USA, 807-818.


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