Tony Wang

455 total citations · 1 hit paper
8 papers, 254 citations indexed

About

Tony Wang is a scholar working on Artificial Intelligence, Sociology and Political Science and Applied Psychology. According to data from OpenAlex, Tony Wang has authored 8 papers receiving a total of 254 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Sociology and Political Science and 2 papers in Applied Psychology. Recurrent topics in Tony Wang's work include Machine Learning in Healthcare (2 papers), Digital Mental Health Interventions (2 papers) and Impact of Technology on Adolescents (2 papers). Tony Wang is often cited by papers focused on Machine Learning in Healthcare (2 papers), Digital Mental Health Interventions (2 papers) and Impact of Technology on Adolescents (2 papers). Tony Wang collaborates with scholars based in United States. Tony Wang's co-authors include Jina Yoon, Joseph Seering, Geoff Kaufman, Amit Uppal, Jessica E. Galarraga, Ioannis Koutroulis, Emilia Apostolova, Robert E. Kraut, Diyi Yang and Gregory W. Wornell and has published in prestigious journals such as New Media & Society, Proceedings of the ACM on Human-Computer Interaction and PubMed.

In The Last Decade

Tony Wang

6 papers receiving 241 citations

Hit Papers

align trajectories

What are hit papers?

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.

Moderator engagement and community development in the age of algorithms

2019 224 citations Joseph Seering, Tony Wang et al. New Media & Society profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Tony Wang United States	4	137	115	108	36	29	8	254
Daniel Delmonaco United States	7	134 1.0×	109 0.9×	131 1.2×	13 0.4×	48 1.7×	12	267
Jane Im United States	9	84 0.6×	60 0.5×	98 0.9×	31 0.9×	27 0.9×	15	234
Tetyana Lokot Ireland	7	80 0.6×	150 1.3×	205 1.9×	35 1.0×	47 1.6×	18	329
Kate Raynes–Goldie Australia	5	40 0.3×	117 1.0×	243 2.3×	28 0.8×	16 0.6×	5	289
Frederic Stutzman United States	5	28 0.2×	82 0.7×	137 1.3×	31 0.9×	10 0.3×	15	191
Richard Campbell United States	10	137 1.0×	45 0.4×	57 0.5×	40 1.1×	16 0.6×	22	337
Travis L. Wagner United States	8	28 0.2×	56 0.5×	76 0.7×	15 0.4×	22 0.8×	42	223
Parisa Roshan United States	10	42 0.3×	39 0.3×	109 1.0×	53 1.5×	11 0.4×	20	244
Sue Aran-Ramspott Spain	7	27 0.2×	188 1.6×	173 1.6×	41 1.1×	51 1.8×	29	321
Marta Pérez Escolar Spain	8	45 0.3×	107 0.9×	138 1.3×	31 0.9×	9 0.3×	32	261

Countries citing papers authored by Tony Wang

Since Specialization

Citations

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

Fields of papers citing papers by Tony Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tony Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Tony Wang. A scholar is included among the top collaborators of Tony Wang 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 Tony Wang. Tony Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Wang, Tony, Amy Bruckman, & Diyi Yang. (2025). The Practice of Online Peer Counseling and the Potential for AI-Powered Support Tools. Proceedings of the ACM on Human-Computer Interaction. 9(2). 1–33.

2.

Wang, Tony, et al.. (2023). Metrics for Peer Counseling: Triangulating Success Outcomes for Online Therapy Platforms. 1–17. 13 indexed citations

3.

Trafimow, David, et al.. (2022). Evaluating the Sampling Precision of Social Identity Related Published Research. 19.

4.

Wang, Tony, et al.. (2021). SDP Methods for Sensitivity-Constrained Privacy Funnel and Information Bottleneck Problems. 49–54. 2 indexed citations

5.

Apostolova, Emilia, et al.. (2019). Towards Reliable ARDS Clinical Decision Support: ARDS Patient Analytics with Free-text and Structured EMR Data.. PubMed. 2019. 228–237. 11 indexed citations

6.

Wang, Tony. (2019). A Service for Provisioning Compute Infrastructure in the Cloud. KTH Publication Database DiVA (KTH Royal Institute of Technology). 1 indexed citations

7.

Seering, Joseph, Tony Wang, Jina Yoon, & Geoff Kaufman. (2019). Moderator engagement and community development in the age of algorithms. New Media & Society. 21(7). 1417–1443. 224 indexed citations breakdown →

8.

Apostolova, Emilia, et al.. (2019). Combining Structured and Free-text Electronic Medical Record Data for Real-time Clinical Decision Support. 66–70. 3 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.

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