Examining Characteristics of Traditional and Twitter Citation - Jung, Hyojung; Lee, Keeheon; Song, Min (Frontiers in Research Metrics and Analytics, 2016)
Social media has attracted the attention of the academic community as an emerging communication channel. This channel opens a new opportunity to measure the impact of social use of scholarly publications in social media (altmetrics) which supplements our understanding on the scholarly impact of publications (bibliometrics). Two different channels, social media and journal, are known to establish various citation patterns statistically. However, thematic difference between altmetrics and bibliometrics structurally and contextually is unknown. Therefore, we perform document co-citation network analysis for structural comparison and topic modeling for contextual comparison. We also suggest Spearman’s correlation for statistical comparison. A case study is done for the publications from Journal of the Association for Information Science and Technology and the tweets mentioning the publications. We identified a weak correlation between scholarly impact and social use of these publications. We also found the structures of the traditional citations and Twitter citations share common but high interest in information retrieval system and impact analysis, while Twitter citations have diverse interest in data mining, network analysis, and information behavior as well. In addition, from content analysis, we found the two citation patterns to have both common and distinct characteristics. Specifically, the topics covered by both citation patterns show intersections and exclusive contexts. In conclusion, the traditional citation patterns and the Twitter citation patterns in Information Science are different statistically, structurally, and contextually. We suspect that intentional and unintentional citing behaviors are the main factor for the thematic difference and will be examined on the future.