Andreu Casas

24 papers receiving 989 citations

Andreu Casas's Hit Papers

Less Annotating, More Classifying: Addressing the Data Scarcity Issue of Supervised Machine Learning with Deep Transfer Learning and BERT-NLI 2023 · 96 citations
960+3+6Years since publication100200300

Peers

Andreu Casas
Comparison fields: 5 of 93
  • General Social Sciences 196
  • Communication 379
  • Political Science and International Relations 280
  • Sociology and Political Science 462
  • Artificial Intelligence 230
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Countries citing papers authored by Andreu Casas

Since Specialization
Citations

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

Fields of papers citing papers by Andreu Casas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Andreu Casas, 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 Andreu Casas Line = papers co-authored together Andreu Casas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Who Leads? Who Follows? Measuring Issue Attention and Agenda Setting by Legislators and the Mass Public Using Social Media Data
Hit paper breakdown →
2019321
2
Large-Scale Computerized Text Analysis in Political Science: Opportunities and Challenges
Hit paper breakdown →
2017182
3 2018105
4
Less Annotating, More Classifying: Addressing the Data Scarcity Issue of Supervised Machine Learning with Deep Transfer Learning and BERT-NLI
Hit paper breakdown →
202396
5 202252
6 202049
7 202138
8 202329
9 201928
10 202124
11 201820
12 202016
13 202213
14
Images as Data for Social Science Research: An Introduction to Convolutional Neural Nets for Image Classification
202013
15 202112
16 202211
17 201610
18 20176
19 20235
20 20225

About Andreu Casas

Andreu Casas is a scholar working on Communication, General Social Sciences, Strategy and Management, Political Science and International Relations and Sociology and Political Science, having authored 25 papers that have together received 1.0k indexed citations. Recurring topics across this work include Social Media and Politics (14 papers), Electoral Systems and Political Participation (9 papers), Computational and Text Analysis Methods (7 papers), Political Influence and Corporate Strategies (7 papers), Misinformation and Its Impacts (6 papers), Hate Speech and Cyberbullying Detection (3 papers), Social and Intergroup Psychology (2 papers) and Media Influence and Politics (2 papers). The work is most often cited by research in General Social Sciences (196 citations), Communication (379 citations), Political Science and International Relations (280 citations), Sociology and Political Science (462 citations) and Artificial Intelligence (230 citations). Andreu Casas has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include John Wilkerson, Joshua Aaron Tucker, Jonathan Nagler, Richard Bonneau, John T. Jost, Pablo Barberá, Patrick J. W. Egan, Magdalena Wojcieszak, Wouter van Atteveldt and Kasper Welbers. Their work appears in journals such as Political Behavior, The Journal of Politics, American Political Science Review, Science Advances and Political Research 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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