Sara Tonelli

2.5k total citations
108 papers, 1.2k citations indexed

About

Sara Tonelli is a scholar working on Artificial Intelligence, Information Systems and Language and Linguistics. According to data from OpenAlex, Sara Tonelli has authored 108 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Artificial Intelligence, 10 papers in Information Systems and 8 papers in Language and Linguistics. Recurrent topics in Sara Tonelli's work include Natural Language Processing Techniques (55 papers), Topic Modeling (53 papers) and Semantic Web and Ontologies (20 papers). Sara Tonelli is often cited by papers focused on Natural Language Processing Techniques (55 papers), Topic Modeling (53 papers) and Semantic Web and Ontologies (20 papers). Sara Tonelli collaborates with scholars based in Italy, Netherlands and United States. Sara Tonelli's co-authors include Paramita Mirza, Stefano Menini, Rachele Sprugnoli, Emanuele Pianta, Giuseppe Riccardi, Giovanni Moretti, Rodolfo Delmonte, Elena Cabrio, Serena Villata and Pierpaolo Vittorini and has published in prestigious journals such as SHILAP Revista de lepidopterología, The American Historical Review and Artificial Intelligence.

In The Last Decade

Sara Tonelli

100 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sara Tonelli Italy 20 1.0k 158 66 58 57 108 1.2k
Omar F. Zaidan United States 14 1.3k 1.3× 157 1.0× 93 1.4× 105 1.8× 41 0.7× 20 1.4k
Tomek Strzalkowski United States 20 1.4k 1.3× 347 2.2× 52 0.8× 62 1.1× 57 1.0× 117 1.6k
Lluís Padró Spain 17 1.3k 1.3× 205 1.3× 143 2.2× 49 0.8× 104 1.8× 95 1.5k
Jan Šnajder Croatia 18 1.1k 1.0× 218 1.4× 37 0.6× 45 0.8× 51 0.9× 110 1.2k
Maciej Piasecki Poland 15 796 0.8× 98 0.6× 150 2.3× 50 0.9× 40 0.7× 115 1.1k
Andréi Popescu-Belis Switzerland 19 996 1.0× 216 1.4× 85 1.3× 145 2.5× 34 0.6× 116 1.2k
Yulia Tsvetkov United States 21 1.4k 1.3× 159 1.0× 80 1.2× 154 2.7× 34 0.6× 96 1.7k
Daniel Duma United Kingdom 9 494 0.5× 103 0.7× 60 0.9× 66 1.1× 31 0.5× 13 800
Monojit Choudhury India 22 1.3k 1.2× 195 1.2× 122 1.8× 147 2.5× 49 0.9× 130 1.6k
Daisuke Kawahara Japan 19 1.3k 1.3× 193 1.2× 39 0.6× 127 2.2× 78 1.4× 139 1.5k

Countries citing papers authored by Sara Tonelli

Since Specialization
Citations

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

Fields of papers citing papers by Sara Tonelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sara Tonelli

This figure shows the co-authorship network connecting the top 25 collaborators of Sara Tonelli. A scholar is included among the top collaborators of Sara Tonelli 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 Sara Tonelli. Sara Tonelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Srba, Ivan, Olesya Razuvayevskaya, Róbert Móro, et al.. (2025). A Survey on Automatic Credibility Assessment Using Textual Credibility Signals in the Era of Large Language Models. ACM Transactions on Intelligent Systems and Technology. 17(2). 1–80.
2.
Lepri, Bruno, et al.. (2024). Do LLMs suffer from Multi-Party Hangover? A Diagnostic Approach to Addressee Recognition and Response Selection in Conversations. Institutional Research Information System (Università degli Studi di Trento). 11210–11233.
3.
Tonelli, Sara, et al.. (2023). Why Don’t You Do It Right? Analysing Annotators’ Disagreement in Subjective Tasks. 2428–2441. 9 indexed citations
4.
Rospocher, Marco, et al.. (2021). On assessing metadata completeness in digital cultural heritage repositories. Digital Scholarship in the Humanities. 36(Supplement_2). ii182–ii188. 3 indexed citations
5.
Aprosio, Alessio Palmero, et al.. (2020). Adding Gesture, Posture and Facial Displays to the PoliModal Corpus of Political Interviews. Language Resources and Evaluation. 4320–4326. 2 indexed citations
6.
Menini, Stefano, et al.. (2017). RAMBLE ON: Tracing Movements of Popular Historical Figures. INFM-OAR (INFN Catania). 77–80. 10 indexed citations
7.
Corcoglioniti, Francesco, Marco Rospocher, Alessio Palmero Aprosio, & Sara Tonelli. (2016). PreMOn: a Lemon Extension for Exposing Predicate Models as Linked Data. Language Resources and Evaluation. 877–884. 6 indexed citations
8.
Menini, Stefano & Sara Tonelli. (2016). Agreement and Disagreement: Comparison of Points of View in the Political Domain.. Institutional Research Information System (Università degli Studi di Trento). 2461–2470. 12 indexed citations
9.
Caselli, Tommaso, et al.. (2016). NLP and Public Engagement: The Case of the Italian School Reform. Language Resources and Evaluation. 401–406. 1 indexed citations
10.
Mirza, Paramita, Rachele Sprugnoli, Sara Tonelli, & Manuela Speranza. (2014). Annotating Causality in the TempEval-3 Corpus. Institutional Research Information System (Università degli Studi di Trento). 10–19. 43 indexed citations
11.
Girardi, Christian, Manuela Speranza, Rachele Sprugnoli, & Sara Tonelli. (2014). CROMER: a Tool for Cross-Document Event and Entity Coreference. Language Resources and Evaluation. 3204–3208. 10 indexed citations
12.
Mirza, Paramita & Sara Tonelli. (2014). An Analysis of Causality between Events and its Relation to Temporal Information. Institutional Research Information System (Università degli Studi di Trento). 2097–2106. 52 indexed citations
13.
Giuliano, Claudio, et al.. (2013). Outsourcing FrameNet to the Crowd. Institutional Research Information System (Università degli Studi di Trento). 2. 742–747. 20 indexed citations
14.
Guerini, Marco, et al.. (2013). FBK: Sentiment Analysis in Twitter with Tweetsted. Joint Conference on Lexical and Computational Semantics. 466–470. 8 indexed citations
15.
Johansson, Richard, et al.. (2012). Improving the Recall of a Discourse Parser by Constraint-based Postprocessing. Language Resources and Evaluation. 2791–2794. 4 indexed citations
16.
Tonelli, Sara & Rodolfo Delmonte. (2011). Desperately Seeking Implicit Arguments in Text. Meeting of the Association for Computational Linguistics. 54–62. 16 indexed citations
17.
Johansson, Richard, et al.. (2011). Shallow Discourse Parsing with Conditional Random Fields. Institutional Research Information System (Università degli Studi di Trento). 1071–1079. 37 indexed citations
18.
Tonelli, Sara & Rodolfo Delmonte. (2010). VENSES++: Adapting a deep semantic processing system to the identification of null instantiations. Meeting of the Association for Computational Linguistics. 5. 296–299. 20 indexed citations
19.
Tonelli, Sara & Emanuele Pianta. (2009). Three Issues in Cross-Language Frame Information Transfer. Recent Advances in Natural Language Processing. 441–448. 1 indexed citations
20.
Tonelli, Sara & Emanuele Pianta. (2008). Frame Information Transfer from English to Italian. Language Resources and Evaluation. 20 indexed citations

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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