Francesco Barbieri
About
In The Last Decade
Francesco Barbieri
40 papers receiving 995 citations
Peers
Comparison fields: 5 of 89
- Artificial Intelligence 763
- Human-Computer Interaction 260
- Computer Vision and Pattern Recognition 134
- Social Psychology 120
- Signal Processing 108
Countries citing papers authored by Francesco Barbieri
This map shows the geographic impact of Francesco Barbieri'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 Francesco Barbieri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Barbieri more than expected).
Fields of papers citing papers by Francesco Barbieri
This network shows the impact of papers produced by Francesco Barbieri. 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 Francesco Barbieri. The network helps show where Francesco Barbieri may publish in the future.
Co-authorship network of co-authors of Francesco Barbieri
This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Barbieri. A scholar is included among the top collaborators of Francesco Barbieri 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 Francesco Barbieri. Francesco Barbieri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 2 | |
| 5 | 6 | |
| 6 | 0 | |
| 7 | 10 | |
| 8 | 112 | |
| 9 | 30 | |
| 10 | 27 | |
| 11 | 97 | |
| 12 | 89 | |
| 13 | What does this emoji mean? A vector space skip-gram model for twitter emojis | 76 |
| 14 | TheRiddlerBot: A next step on the ladder towards creative Twitter bots. | 5 |
| 15 | Is this Tweet Satirical? A Computational Approach for Satire Detection in Spanish | 15 |
| 16 | How Topic Biases Your Results? A Case Study of Sentiment Analysis and Irony Detection in Italian | 1 |
| 17 | Do we criticise (and laugh) in the same way? automatic detection of multi-lingual satirical news in twitter | 12 |
| 18 | 59 | |
| 19 | Modelling Irony in Twitter: Feature Analysis and Evaluation | 18 |
| 20 | Automatic Detection of Irony and Humour in Twitter. | 43 |
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.