Massimo Poesio
About
In The Last Decade
Massimo Poesio
209 papers receiving 4.5k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Artificial Intelligence 4.2k
- Language and Linguistics 502
- Experimental and Cognitive Psychology 441
- Information Systems 398
- Cognitive Neuroscience 370
Countries citing papers authored by Massimo Poesio
This map shows the geographic impact of Massimo Poesio'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 Massimo Poesio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Poesio more than expected).
Fields of papers citing papers by Massimo Poesio
This network shows the impact of papers produced by Massimo Poesio. 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 Massimo Poesio. The network helps show where Massimo Poesio may publish in the future.
Co-authorship network of co-authors of Massimo Poesio
This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Poesio. A scholar is included among the top collaborators of Massimo Poesio based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Massimo Poesio. Massimo Poesio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 20 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 19 | |
| 9 | 40 | |
| 10 | Metrics of games-with-a-purpose for NLP applications | 4 |
| 11 | 34 | |
| 12 | Predicting Brexit: Classifying Agreement is Better than Sentiment and Pollsters | 13 |
| 13 | BART goes multilingual: The UniTN / Essex submission to the CoNLL-2012 Shared Task | 12 |
| 14 | Domain-specific vs. Uniform Modeling for Coreference Resolution | 7 |
| 15 | Lexical vs. Surface Features in Deceptive Language Analysis | 8 |
| 16 | Anaphoric Annotation of Wikipedia and Blogs in the Live Memories Corpus | 23 |
| 17 | WB-JRC-UT's Participation in TAC 2009: Update Summarization and AESOP Tasks. | 8 |
| 18 | 23 | |
| 19 | Acquiring Bayesian Networks from Text | 15 |
| 20 | 2 |
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.