Ted Striphas

21 papers receiving 702 citations

Ted Striphas's Hit Papers

Algorithmic culture 2015 · 269 citations
2690+4+8Years since publication50100150200250

Peers

Ted Striphas
Comparison fields: 5 of 95
  • Communication 164
  • Computer Science Applications 70
  • Safety Research 103
  • Music 36
  • Gender Studies 86
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Wendy Hui Kyong Chun Canada
Simone Natale United Kingdom
Siva Vaidhyanathan United States
Ignacio Siles Costa Rica
Tim Jordan United Kingdom
Geert Lovink Netherlands
Lisa Gitelman Switzerland
Blake Hallinan Israel
Mizuko Ito United States
Lars Nyre Norway
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Citations per year

Countries citing papers authored by Ted Striphas

Since Specialization
Citations

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

Fields of papers citing papers by Ted Striphas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside Ted Striphas, 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 Ted Striphas Line = papers co-authored together Ted Striphas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Recommended for you: The Netflix Prize and the production of algorithmic culture
Hit paper breakdown →
2014293
2
Algorithmic culture
Hit paper breakdown →
2015269
3 200681
4 201026
5 202116
6 200316
7 201012
8 199811
9 200211
10 20189
11 20068
12 19986
13 20095
14 20065
15 20114
16 20134
17 20134
18 20172
19 20012
20
Banality, Book Publishing, and the Everyday Life of Cultural Studies
20002

About Ted Striphas

Ted Striphas is a scholar working on Sociology and Political Science, Literature and Literary Theory, Marketing, Philosophy and Communication, having authored 22 papers that have together received 787 indexed citations. Recurring topics across this work include Copyright and Intellectual Property (3 papers), Rhetoric and Communication Studies (3 papers), Discourse Analysis in Language Studies (2 papers), Social and Cultural Dynamics (2 papers), Ethics and Social Impacts of AI (2 papers), University Challenges and Reforms (2 papers), Innovative Human-Technology Interaction (2 papers) and Social Media and Politics (1 paper). The work is most often cited by research in Communication (164 citations), Computer Science Applications (70 citations), Safety Research (103 citations), Music (36 citations) and Gender Studies (86 citations). Ted Striphas has collaborated with scholars based in United States, Ireland and Russia. Frequent co-authors include Blake Hallinan, Gregory J. Shepherd, Jeffrey St. John, John Nguyet Erni, Kembrew McLeod, Mark Hayward and Phaedra C. Pezzullo. Their work appears in journals such as Cultural Studies, Communication and Critical/Cultural Studies, Critical Studies in Media Communication, International Journal of Cultural Studies and Rhetoric Society Quarterly.

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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