Fernando Batista

1.2k citations
95 papers · 618 · h-index 14

Impact in

    • Natural Language Processing Techniques
    • Topic Modeling
    • Speech Recognition and Synthesis
    • Speech and dialogue systems
    • Sentiment Analysis and Opinion Mining
    • Advanced Text Analysis Techniques
  • Marketing top 10%

Papers in

Fernando Batista

82 papers receiving 553 citations

Peers

Fernando Batista
Comparison fields: 5 of 92
  • Artificial Intelligence 391
  • Marketing 52
  • Experimental and Cognitive Psychology 69
  • Tourism, Leisure and Hospitality Management 7
  • Signal Processing 46
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Citations per field
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Citations per year

Countries citing papers authored by Fernando Batista

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Batista

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 95 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201237
2 202030
3 201830
4 200829
5 201729
6 201827
7 201925
8 201422
9 201519
10
Sentiment Analysis and Topic Classification based on Binary Maximum Entropy Classifiers
201318
11 200718
12 201218
13 201417
14 202213
15 201911
16 20149
17 20149
18 20188
19
[Double blind clinical trial on the use of ultra-levure in the prophylaxis of antibiotic induced gastro-intestinal and mucocutaneous disorders].
19828
20 20138

About Fernando Batista

Fernando Batista is a scholar working on Artificial Intelligence, Sociology and Political Science, Experimental and Cognitive Psychology, Information Systems and Communication, having authored 95 papers that have together received 618 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (33 papers), Speech and dialogue systems (23 papers), Topic Modeling (16 papers), Speech Recognition and Synthesis (14 papers), Digital Marketing and Social Media (13 papers), Sentiment Analysis and Opinion Mining (11 papers), Phonetics and Phonology Research (10 papers) and Complex Network Analysis Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (391 citations), Marketing (52 citations), Experimental and Cognitive Psychology (69 citations), Tourism, Leisure and Hospitality Management (7 citations) and Signal Processing (46 citations). Fernando Batista has collaborated with scholars based in Portugal, United States and Jordan. Frequent co-authors include Ricardo Ribeiro, Isabel Trancoso, João Paulo Carvalho, Nuno Mamede, Helena Moniz, Hugo Rosa, Ana de Almeida, Luís Nunes, Nuno António and Diamantino Caseiro. Their work appears in journals such as Language Resources and Evaluation, Social Network Analysis and Mining, Speech Communication, Expert Systems with Applications and Journal of Information Science.

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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