Tim Hwang

915 citations
14 papers · 411 indexed · h-index 9

Impact in

Papers in

Tim Hwang

13 papers receiving 376 citations

Peers

Tim Hwang
Comparison fields: 5 of 79
  • Communication 101
  • Marketing 81
  • Sociology and Political Science 239
  • Safety Research 40
  • Automotive Engineering 40
Replace Carolina Salge with:
Carolina Salge United States
Qiqi Jiang China
Xinru Page United States
Sangyong Han South Korea
Nina Gerber Germany
Elizabeth S. Veinott United States
Natalie Gerhart United States
Ryan Wesslen United States
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Tim Hwang relative to Carolina Salge United States Carolina Salge's profile →
Citations per field
00.5×10×
Carolina Salge · 1×
Citations per year

Countries citing papers authored by Tim Hwang

Since Specialization
Citations

This map shows the geographic impact of Tim Hwang'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 Tim Hwang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Hwang more than expected).

Fields of papers citing papers by Tim Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tim Hwang. 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 Tim Hwang. The network helps show where Tim Hwang may publish in the future.

Co-authors

The 20 scholars most cited alongside Tim Hwang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tim Hwang Line = papers co-authored together Tim Hwang links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2020125
2 201786
3 201269
4 201842
5
Discriminating Tastes: Customer Ratings as Vehicles for Bias
201619
6
Applying theory to practice: CARE’s journey piloting social norms measures for gender programming.
201719
7
Subprime Attention Crisis: Advertising and the Time Bomb at the Heart of the Internet
202015
8 201513
9 20179
10 20076
11 20174
12 20152
13 20141
14
Praise the Machine! Punish the Human!
20151

About Tim Hwang

Tim Hwang is a scholar working on Communication, Sociology and Political Science, Information Systems, Artificial Intelligence and Safety Research, having authored 14 papers that have together received 411 indexed citations. Recurring topics across this work include Social Media and Politics (2 papers), Hate Speech and Cyberbullying Detection (2 papers), Wikis in Education and Collaboration (2 papers), Digital Economy and Work Transformation (2 papers), Evacuation and Crowd Dynamics (1 paper), Spam and Phishing Detection (1 paper), Sharing Economy and Platforms (1 paper) and Advanced Malware Detection Techniques (1 paper). The work is most often cited by research in Communication (101 citations), Marketing (81 citations), Sociology and Political Science (239 citations), Safety Research (40 citations) and Automotive Engineering (40 citations). Tim Hwang has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Solon Barocas, Alex Rosenblat, Karen Levy, Ian Pearce, Francis Fukuyama, Nathaniel Persily, Samuel Woolley, Rasmus Kleis Nielsen, Alexandra Siegel and Chloe Wittenberg. Their work appears in journals such as Policy & Internet, interactions, Journal of Visual Culture, Network Security and Cambridge University Press eBooks.

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.

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