Highly tweeted science articles: who tweets them? An analysis of Twitter user profile descriptions

In this study we examined who tweeted academic articles that had at least one Finnish author or co-author affiliation and that had high altmetric counts on Twitter. In this investigation of national level altmetrics we chose the most tweeted scientific articles from four broad areas of science (Agricultural, Engineering and Technological Sciences; Medical and Health Sciences; Natural Sciences; Social Sciences and Humanities). By utilizing both quantitative and qualitative methods of analysis, we studied the data using research techniques such as keyword categorization, co-word analysis and content analysis of user profile descriptions. Our results show that contrary to a random sample of Twitter users, users who tweet academic articles describe themselves more factually and by emphasizing their occupational expertise rather than personal interests. The more field-specific the articles were, the more research-related descriptions dominated in Twitter profile descriptions. We also found that scientific articles were tweeted to promote ideological views especially in instances where the article represented a topic that divides general opinion.

[1]  K. Monroe,et al.  NARRATIVE IN POLITICAL SCIENCE , 1998 .

[2]  Michael F. Dahlstrom.  Using narratives and storytelling to communicate science with nonexpert audiences , 2014, Proceedings of the National Academy of Sciences.

[3]  Kim Holmberg,et al.  The Meaning of Altmetrics , 2014 .

[4]  Tara J Brigham.  An Introduction to Altmetrics , 2014, Medical reference services quarterly.

[5]  Hui Wu,et al.  Correlation and Interaction Visualization of Altmetric Indicators Extracted From Scholarly Social Network Activities: Dimensions and Structure , 2013, Journal of medical Internet research.

[6]  Maurice Vergeer,et al.  Is the voter only a tweet away? Micro blogging during the 2009 European Parliament election campaign in the Netherlands , 2011, First Monday.

[7]  Paul Groth,et al.  The Altmetrics Collection , 2012, PloS one.

[8]  F. Badenschier,et al.  Issue Selection in Science Journalism: Towards a Special Theory of News Values for Science News? , 2012 .

[9]  Qing Ke,et al.  A systematic identification and analysis of scientists on Twitter , 2016, PloS one.

[10]  M. Patton,et al.  Qualitative evaluation and research methods , 1992 .

[11]  유창조.  Naturalistic Inquiry , 2022, The SAGE Encyclopedia of Research Design.

[12]  Muhammad Imran,et al.  Understanding Types of Users on Twitter , 2014, ArXiv.

[13]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[14]  魏屹东,et al.  Scientometrics , 2018, Encyclopedia of Big Data.

[15]  Mike Thelwall,et al.  Tweeting Links to Academic Articles , 2013 .

[16]  Andrew Carstairs McCarthy.  An introduction to English morphology: words and their structure. , 2002 .

[17]  Hsiu-Fang Hsieh,et al.  Three Approaches to Qualitative Content Analysis , 2005, Qualitative health research.

[18]  Scott H. Burton,et al.  Evaluating Social Media’s Capacity to Develop Engaged Audiences in Health Promotion Settings , 2013, Health Promotion Practice.

[19]  M. Patton.  Qualitative research and evaluation methods , 1980 .

[20]  Mark Kats,et al.  Tweeting the Meeting: An In-Depth Analysis of Twitter Activity at Kidney Week 2011 , 2012, PloS one.

[21]  David Gunnarsson Lorentzen,et al.  Twitter conversation patterns related to research papers , 2016, Inf. Res..

[22]  W. Bennett,et al.  Social Media and the Organization of Collective Action: Using Twitter to Explore the Ecologies of Two Climate Change Protests , 2011 .

[23]  R. Lambiotte,et al.  Random Walks, Markov Processes and the Multiscale Modular Organization of Complex Networks , 2008, IEEE Transactions on Network Science and Engineering.

[24]  Yan Zhang,et al.  Qualitative Analysis of Content by , 2005 .

[25]  Yijun Liu,et al.  Analyzing brain networks with PCA and conditional Granger causality , 2009, Human brain mapping.

[26]  Barbara M. Wildemuth,et al.  Applications of Social Research Methods to Questions in Information and Library Science , 2009 .

[27]  Andrew Carstairs-McCarthy.  An Introduction to English Morphology: Words and Their Structure , 2018 .

[28]  Evaggelia Pitoura,et al.  How people describe themselves on Twitter , 2013, DBSocial '13.

[29]  Sune Lehmann,et al.  Understanding the Demographics of Twitter Users , 2011, ICWSM.

[30]  Lutz Bornmann.  What do altmetrics counts mean? A plea for content analyses , 2016, J. Assoc. Inf. Sci. Technol..

[31]  Simone Rödder,et al.  The Sciences’ Media Connection – Public Communication and its Repercussions , 2012 .

[32]  Gunther Eysenbach,et al.  Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact , 2011, Journal of medical Internet research.

[33]  Jason Priem,et al.  How and why scholars cite on Twitter , 2010, ASIST.

[34]  Vincent Larivière,et al.  Astrophysicists on Twitter: An in-depth analysis of tweeting and scientific publication behavior , 2014, Aslib J. Inf. Manag..

[35]  Stephanie J. Bird.  Socially Responsible Science Is More than “Good Science” , 2014, Journal of microbiology & biology education.

[36]  Robert Jäschke,et al.  Identifying and analyzing researchers on twitter , 2014, WebSci '14.

[37]  Mike Thelwall,et al.  Disciplinary differences in Twitter scholarly communication , 2014, Scientometrics.

[38]  Jean Pierre Courtial,et al.  A coword analysis of scientometrics , 1994, Scientometrics.