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

被引:0
作者
Julia Vainio
Kim Holmberg
机构
[1] University of Turku,Research Unit for the Sociology of Education
来源
Scientometrics | 2017年 / 112卷
关键词
Twitter; Twitter profile; Altmetrics; Scholarly communication;
D O I
暂无
中图分类号
学科分类号
摘要
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.
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页码:345 / 366
页数:21
相关论文
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  • [1] Badenschier F(2012)Issue selection in science journalism: Towards a special theory of news values for science news? Sociology of the Sciences Yearbook 28 273-289
  • [2] Holger W(2014)Socially responsible science is more than “good science” Journal of Microbiology & Biology Education 15 169-172
  • [3] Bird SJ(2008)Fast unfolding of communities in large networks Journal of Statistical Mechanics: Theory and Experiment 10008 6-260
  • [4] Blondel VD(2016)What do altmetrics counts mean? A plea for content analyses Journal of the Association for Information Science and Technology 31 251-13620
  • [5] Guillaume J-L(1994)A coword analysis of scientometrics Scientometrics 111 13614-296
  • [6] Lambiotte R(2014)Using narratives and storytelling to communicate science with nonexpert audiences Proceedings of the National Academy of Sciences of the United States of America 66 279-1288
  • [7] Lefebvre E(2012)Tweeting the meeting: An in-depth analysis of Twitter activity at kidney week 2011 PLoS ONE 15 1277-862
  • [8] Bornmann L(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 60 858-162
  • [9] Courtial JP(2014)Astrophysicists on Twitter: An in-depth analysis of tweeting and scientific publication behavior Aslib Journal of Information Management 14 157-331
  • [10] Dahlstrom MF(2014)Three approaches to qualitative content analysis Disciplinary differences in Twitter scholarly communication. 1 315-215