Investigating the Characteristics and Research Impact of Sentiments in Tweets with Links to Computer Science Research Papers

  • Aravind Sesagiri RaamkumarEmail author
  • Savitha Ganesan
  • Keerthana Jothiramalingam
  • Muthu Kumaran Selva
  • Mojisola Erdt
  • Yin-Leng Theng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11279)


Research papers are often shared in Twitter to facilitate better readership. Tweet counts are embedded in journal websites and academic databases, to emphasize the impact of papers in social media. However, more number of tweets per paper is doubted as an indicator of research quality. Hence, there is a need to look at the intrinsic factors in tweets. Sentiment is one of such factors. Earlier studies have shown that neutral sentiment is predominantly found in tweets with links to research papers. In this study, the main intention was to have a closer look at the non-neutral sentiments in tweets to understand whether there is some scope for using such tweets in measuring the interim quality of the associated research papers. Tweets of 53,831 computer science papers from the Microsoft Academic Graph (MAG) dataset were extracted for sentiment classification. The non-neutral sentiment keywords and the attributed aspects of the papers were manually identified. Findings indicate that although neutral sentiments are majorly found in tweets, the research impact of papers which had all three sentiments was better than papers which had only neutral sentiment, in terms of both bibliometrics and altmetrics. Implications for future studies are also discussed.


Twitter Tweet sentiments Research impact Computer science Research metrics 



The research project “Altmetrics: Rethinking And Exploring New Ways Of Measuring Research” is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Science of Research, Innovation and Enterprise programme (SRIE Award No. NRF2014-NRF-SRIE001-019).


  1. 1.
    Viviani, M., Pasi, G.: Credibility in social media: opinions, news, and health information - a survey. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 7, e1209 (2017)Google Scholar
  2. 2.
    Laakso, M., Welling, P., Bukvova, H., Nyman, L., Björk, B.-C., Hedlund, T.: The development of open access journal publishing from 1993 to 2009. PLoS ONE 6, e20961 (2011)CrossRefGoogle Scholar
  3. 3.
    Liu, X.Z., Fang, H.: What we can learn from tweets linking to research papers. Scientometrics 111, 349–369 (2017)CrossRefGoogle Scholar
  4. 4.
    Haustein, S., Larivière, V.: The use of bibliometrics for assessing research: possibilities, limitations and adverse effects. In: Welpe, I.M., Wollersheim, J., Ringelhan, S., Osterloh, M. (eds.) Incentives and Performance, pp. 121–139. Springer, Cham (2015). Scholar
  5. 5.
    Priem, J., Taraborelli, D., Groth, P., Neylon, C.: Altmetrics: a manifestoitle.
  6. 6.
    Veletsianos, G., Kimmons, R.: Scholars in an increasingly open and digital world: how do education professors and students use Twitter? Internet High. Educ. 30, 1–10 (2016)CrossRefGoogle Scholar
  7. 7.
    Mohammadi, E., Thelwall, M., Kwasny, M., Holmes, K.L.: Academic information on Twitter: a user survey. PLoS ONE 13, e0197265 (2018)CrossRefGoogle Scholar
  8. 8.
    Robinson-Garcia, N., Costas, R., Isett, K., Melkers, J., Hicks, D.: The unbearable emptiness of tweeting—About journal articles. PLoS ONE 12, e0183551 (2017)CrossRefGoogle Scholar
  9. 9.
    Merton, R.K.: The Matthew effect in science. Science 159, 59–63 (1968)CrossRefGoogle Scholar
  10. 10.
    Thelwall, M.: Why do papers have many Mendeley readers but few scopus-indexed citations and vice versa? J. Librariansh. Inf. Sci. 49, 144–151 (2017)CrossRefGoogle Scholar
  11. 11.
    Costas, R., Zahedi, Z., Wouters, P.: Do “Altmetrics” correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective. J. Assoc. Inf. Sci. Technol. 66, 2003–2019 (2015)CrossRefGoogle Scholar
  12. 12.
    Ortega, J.L.: Relationship between altmetric and bibliometric indicators across academic social sites: the case of CSIC’s members. J. Informetr. 9, 39–49 (2015)CrossRefGoogle Scholar
  13. 13.
    Chew, C., Eysenbach, G.: Pandemics in the age of Twitter: content analysis of tweets during the 2009 H1N1 outbreak. PLoS ONE 5, e14118 (2010)CrossRefGoogle Scholar
  14. 14.
    Small, T.A.: What the Hashtag? A content analysis of Canadian politics on Twitter. Inf. Commun. Soc. 14, 872–895 (2011)CrossRefGoogle Scholar
  15. 15.
    Pang, B., Lee, L.: Opinion mining and sentiment analysis. Found. Trends® Inf. Retr. 2, 1–135 (2008)CrossRefGoogle Scholar
  16. 16.
    Bing, L.: Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Springer, Heidelberg (2007). Scholar
  17. 17.
    Kouloumpis, E., Wilson, T., Moore, J.: Twitter sentiment analysis: the good the dad and the OMG! In: Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media (2011)Google Scholar
  18. 18.
    Thakkar, H., Patel, D.: Approaches for sentiment analysis on Twitter: a state-of-art study (2015)Google Scholar
  19. 19.
    Thelwall, M., Tsou, A., Weingart, S., Holmberg, K., Haustein, S.: Tweeting links to academic articles. Cybermetrics Int. J. Sci. Inf. Bibliometr. 17, 1–8 (2013)Google Scholar
  20. 20.
    Friedrich, N., Bowman, T.D., Stock, W.G., Haustein, S.: Adapting sentiment analysis for tweets linking to scientific papers (2015)Google Scholar
  21. 21.
    Friedrich, N., Bowman, T.D., Haustein, S.: Do tweets to scientific articles contain positive or negative sentiments? In: The 2015 Altmetrics Workshop, Amsterdam (2015)Google Scholar
  22. 22.
    Sinha, A., et al.: An overview of microsoft academic service (MAS) and applications. In: Proceedings of the 24th International Conference on World Wide Web - WWW 2015 Companion, pp. 243–246. ACM Press, New York (2015)Google Scholar
  23. 23.
    Chu, Z., Gianvecchio, S., Wang, H., Jajodia, S.: Who is tweeting on Twitter: human, bot, or cyborg? In: Proceedings of the 26th Annual Computer Security Applications Conference on - ACSAC 2010, p. 21. ACM Press, New York (2010)Google Scholar
  24. 24.
    Charmaz, K., Belgrave, L.L.: Grounded theory. In: The Blackwell Encyclopedia of Sociology. Wiley, Oxford (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Wee Kim Wee School of Communication and InformationNanyang Technological UniversitySingaporeSingapore

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