Saiph Savage

1.6k citations
47 papers · 899 indexed · 1 hit paper · h-index 14

Saiph Savage

41 papers receiving 867 citations

Hit Papers

A Data-Driven Analysis of Workers' Earnings on Amazon Mec...299201820262020202350100150200250

Peers

Saiph Savage
Comparison fields: 5 of 105
  • Computer Science Applications 233
  • Human-Computer Interaction 119
  • Human Factors and Ergonomics 38
  • Communication 98
  • Safety Research 86
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Alexandra To United States
Joel Ross United States
Austin L. Toombs United States
Andreas Janson Germany
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Benjamin V. Hanrahan United States
Xuesong Zhai China
Niloufar Salehi United States
Nora McDonald United States
Rod D. Roscoe United States
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Citations per field
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Citations per year

Countries citing papers authored by Saiph Savage

Since Specialization
Citations

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

Fields of papers citing papers by Saiph Savage

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Saiph Savage, 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 Saiph Savage Line = papers co-authored together Saiph Savage links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20253
2 20240
3 20230
4 20229
5 20223
6 20210
7 20203
8
Solidarity and A.I. for Transitioning to Crowd Work during COVID-19
20201
9 202026
10 20191
11 201926
12 201829
13 201829
14 201721
15
Social Media, Civic Engagement and the Slacktivism Hypothesis: Dig Data Lessons from Mexico's 'El Bronco'
201610
16 20161
17
Political bots and the manipulation of public opinion in Venezuela
201577
18 201511
19 20154
20 200833

About Saiph Savage

Saiph Savage is a scholar working on Computer Science Applications, Human-Computer Interaction and Communication, having authored 47 papers that have together received 899 indexed citations. Recurring topics across this work include Mobile Crowdsensing and Crowdsourcing (23 papers), Innovative Human-Technology Interaction (10 papers), Digital Economy and Work Transformation (7 papers), Open Source Software Innovations (5 papers), Tactile and Sensory Interactions (5 papers), Social Media and Politics (4 papers), Misinformation and Its Impacts (4 papers) and Auction Theory and Applications (3 papers). The work is most often cited by research in Computer Science Applications (233 citations), Human-Computer Interaction (119 citations) and Human Factors and Ergonomics (38 citations). Saiph Savage has collaborated with scholars based in United States, Mexico and United Kingdom. Frequent co-authors include Jeffrey P. Bigham, Kristy Milland, Kotaro Hara, Abigail Adams, Chris Callison-Burch, Andrés Monroy‐Hernández, Jessica Hammer, Joseph Seering, Philip N. Howard and C. Chiang. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Communications of the ACM, Personal and Ubiquitous Computing, Computer Supported Cooperative Work (CSCW) and Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies.

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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