Understanding the Twitter Usage of Science Citation Index (SCI) Journals

Abstract

This paper investigates the Twitter interaction patterns of journals from the Science Citation Index (SCI) of Master Journal List (MJL). A total of 953,253 tweets extracted from 857 journal accounts, were analyzed in this study. Findings indicate that SCI journals interacted more with each other but much less with journals from other citation indices. The network structure of the communication graph resembled a tight crowd network, with Nature journals playing a major part. Information sources such as news portals and scientific organizations were mentioned more in tweets, than academic journal Twitter accounts. Journals with high journal impact factors (JIFs) were found to be prominent hubs in the communication graph. Differences were found between the Twitter usage of SCI journals with Humanities and Social Sciences (HSS) journals.

TweetPap: A Dataset to Study the Social Media Discourse of Scientific Papers

“…Since the same paper can be mentioned in multiple tweets, we present a cumulative count of retweet/like from all the tweets corresponding to that paper. In the end, we obtain a dataset with statistics and attributes defined in Table I and Figure 1 respectively, along with yearly citations and tweet information such as text and yearly retweets data (pulled from Twitter API 5 ). 1 github.com/Jefferson-Henrique/GetOldTweets-python 2 Only 16,435 tweets were retrieved using title matching 3 github.com/SMAPPNYU/urlExpander 4 https://arXiv.org/help/arXiv identifier 5 https://python-twitter.readthedocs.io/en/latest/ arXiv:2106.07213v1 [cs.DL] 14 Jun 2021 "arXiv ID: <id>" "Citation: <map[year→int]>" "Publication Year: <int>" "Retweet: <map[year→int]>" "Tweet IDs: <list[int]>" "Likes: <int>" "Links: <list[string]>" "Users: <list[string]>"…”

“…Research institutes also use research impact to assess the performance of faculty members, make grant allocations, set policies, and recruit new members [3]. The eagerness to improve research impact led researchers to "push" their work on social media platforms like Twitter for greater reach [4], [5]. Existing studies have attempted to capture the discourse of scientific knowledge through social media platforms by analyzing the number of mentions of a publication on Twitter in small-scale datasets created manually or using surveys and analytics platforms [2]- [4], [6] whereas large-scale datasets lack analysis with citation data [5].…”