Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Community Intelligence and Social Media Services: A Rumor Theoretic Analysis of Tweets During Social Crises1
2013439 citationsOnook Oh, Manish Agrawal et al.MIS Quarterlyprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Onook Oh's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Onook Oh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Onook Oh more than expected).
This network shows the impact of papers produced by Onook Oh. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Onook Oh. The network helps show where Onook Oh may publish in the future.
Co-authorship network of co-authors of Onook Oh
This figure shows the co-authorship network connecting the top 25 collaborators of Onook Oh.
A scholar is included among the top collaborators of Onook Oh based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Onook Oh. Onook Oh is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Aghakhani, Navid, Onook Oh, & Dawn G. Gregg. (2017). Beyond the Review Sentiment: The Effect of Review Accuracy and Review Consistency on Review Usefulness. Journal of the Association for Information Systems.5 indexed citations
7.
Oh, Onook, et al.. (2016). Understanding Sociomateriality through the Lens of Assemblage Theory: Examples from Police Body-Worn Cameras. International Conference on Information Systems.5 indexed citations
8.
Nguyen, Cuong Duc, Nargess Tahmasbi, Triparna de Vreede, et al.. (2015). Participant Engagement in Community Crowdsourcing. Journal of the Association for Information Systems.11 indexed citations
9.
Tahmasbi, Nargess, et al.. (2013). Crowdsourcing: A snapshot of published research. Journal of the Association for Information Systems. 962–975.21 indexed citations
10.
Nguyen, Cuong Duc, et al.. (2013). Crowdsourcing as Lego: Unpacking the Building Blocks of Crowdsourcing Collaboration Processes. Journal of the Association for Information Systems. 984–992.5 indexed citations
Oh, Onook, Nargess Tahmasbi, H. Raghav Rao, & Gert‐Jan de Vreede. (2012). A SOCIOTECHNICAL VIEW OF INFORMATION DIFFUSION AND SOCIAL CHANGES : FROM REPRINT TO RETWEET. Journal of the Association for Information Systems. 3686–3696.2 indexed citations
15.
Oh, Onook, et al.. (2012). Collective Sense-Making through the Twitter Service during the 2011 Egypt Revolution. International Conference on Information Systems.4 indexed citations
Oh, Onook, K. Hazel Kwon, Manish Agrawal, & Hengyi Rao. (2011). Choice of information: A study of twitter news sharing during the 2009 israel-gaza conflict. Journal of the Association for Information Systems. 953–964.2 indexed citations
18.
Oh, Onook, K. Hazel Kwon, & H. Raghav Rao. (2010). AN EXPLORATION OF SOCIAL MEDIA IN EXTREME EVENTS: RUMOR THEORY AND TWITTER DURING THE HAITI EARTHQUAKE 2010. International Conference on Information Systems. 231.129 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.