ML Tlachac

31 papers receiving 291 citations

Peers

ML Tlachac
Comparison fields: 5 of 46
  • Applied Psychology 141
  • Experimental and Cognitive Psychology 149
  • Social Psychology 163
  • Artificial Intelligence 84
  • Applied Microbiology and Biotechnology 4
Replace Anastasia Pampouchidou with:
Anastasia Pampouchidou France
Reynaldo Morillo United States
Brian Stasak Australia
Kara Chappie United States
Kennedy Opoku Asare Finland
Shweta Ware United States
Rui Su China
Victor R. Martínez United States
Yuanyuan Xue China
Alban Maxhuni Italy
ML Tlachac relative to Anastasia Pampouchidou France Anastasia Pampouchidou's profile →
Citations per field
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Anastasia Pampouchidou · 1×
Citations per year

Countries citing papers authored by ML Tlachac

Since Specialization
Citations

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

Fields of papers citing papers by ML Tlachac

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside ML Tlachac, 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 ML Tlachac Line = papers co-authored together ML Tlachac links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202040
2 202132
3 202222
4 202120
5 202217
6 202017
7 201914
8 202014
9 202113
10 202212
11 202210
12 202110
13 202210
14 20228
15 20247
16 20227
17 20206
18 20186
19 20225
20 20234

About ML Tlachac

ML Tlachac is a scholar working on Experimental and Cognitive Psychology, Social Psychology, Applied Psychology, Artificial Intelligence and Clinical Psychology, having authored 34 papers that have together received 297 indexed citations. Recurring topics across this work include Digital Mental Health Interventions (18 papers), Mental Health via Writing (17 papers), Mental Health Research Topics (15 papers), Sentiment Analysis and Opinion Mining (4 papers), Emotion and Mood Recognition (4 papers), Bacterial Identification and Susceptibility Testing (3 papers), Voice and Speech Disorders (2 papers) and Music and Audio Processing (2 papers). The work is most often cited by research in Applied Psychology (141 citations), Experimental and Cognitive Psychology (149 citations), Social Psychology (163 citations), Artificial Intelligence (84 citations) and Applied Microbiology and Biotechnology (4 citations). ML Tlachac has collaborated with scholars based in United States, Chile and Switzerland. Frequent co-authors include Elke A. Rundensteiner, Ermal Toto, Francis L. Stevens, Katherine L. Dixon–Gordon, Tingting Zhao, George Price, Lane Harrison, Michael V. Heinz, Nicholas C. Jacobson and Randy Paffenroth. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, IEEE Transactions on Affective Computing, Discrete Mathematics & Theoretical Computer Science and Sexuality & Culture.

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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