Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter
2019509 citationsValerio Basile, Cristina Bosco et al.BOA (University of Milano-Bicocca)profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Manuela Sanguinetti
Since
Specialization
Citations
This map shows the geographic impact of Manuela Sanguinetti'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 Manuela Sanguinetti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manuela Sanguinetti more than expected).
Fields of papers citing papers by Manuela Sanguinetti
This network shows the impact of papers produced by Manuela Sanguinetti. 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 Manuela Sanguinetti. The network helps show where Manuela Sanguinetti may publish in the future.
Co-authorship network of co-authors of Manuela Sanguinetti
This figure shows the co-authorship network connecting the top 25 collaborators of Manuela Sanguinetti.
A scholar is included among the top collaborators of Manuela Sanguinetti 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 Manuela Sanguinetti. Manuela Sanguinetti is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Sanguinetti, Manuela, Cristina Bosco, Özlem Çetinoğlu, et al.. (2020). Treebanking User-Generated Content: A Proposal for a Unified Representation in Universal Dependencies. Language Resources and Evaluation. 5240–5250.9 indexed citations
Sanguinetti, Manuela, et al.. (2020). Annotating Errors and Emotions in Human-Chatbot Interactions in Italian. Institutional Research Information System University of Turin (University of Turin). 148–159.4 indexed citations
9.
Cignarella, Alessandra Teresa, Manuela Sanguinetti, Cristina Bosco, & Paolo Rosso. (2020). Marking Irony Activators in a Universal Dependencies Treebank: The Case of an Italian Twitter Corpus. Language Resources and Evaluation. 5098–5105.1 indexed citations
Basile, Valerio, Cristina Bosco, Elisabetta Fersini, et al.. (2019). SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter. BOA (University of Milano-Bicocca). 54–63.509 indexed citations breakdown →
13.
Bosco, Cristina, et al.. (2019). Error analysis in a hate speech detection task: The case of Haspeede-TW at Evalita 2018. Institutional Research Information System University of Turin (University of Turin). 2481. 1–6.3 indexed citations
14.
Lai, Mirko, Valerio Basile, Cataldo Musto, et al.. (2019). Computational Linguistics Against Hate: Hate Speech Detection and Visualization on Social Media in the "Contro L'Odio" Project.. 2481. 1–6.10 indexed citations
15.
Sanguinetti, Manuela, Fabio Poletto, Cristina Bosco, Viviana Patti, & Marco Antonio Stranisci. (2018). An Italian Twitter Corpus of Hate Speech against Immigrants. Language Resources and Evaluation. 1–8.108 indexed citations
16.
Sanguinetti, Manuela, et al.. (2018). PoSTWITA-UD: an Italian Twitter Treebank in Universal Dependencies.. Language Resources and Evaluation. 1768–1775.31 indexed citations
Bosco, Cristina, et al.. (2014). Detecting Happiness in Italian Tweets: Towards an Evaluation Dataset for Sentiment Analysis in Felicittà. 56–63.9 indexed citations
19.
Sanguinetti, Manuela, Cristina Bosco, & Leonardo Lesmo. (2013). Dependency and Constituency in Translation Shift Analysis. Institutional Research Information System University of Turin (University of Turin). 282–291.2 indexed citations
20.
Bosco, Cristina, Manuela Sanguinetti, & Leonardo Lesmo. (2012). The Parallel-TUT: a multilingual and multiformat treebank. Language Resources and Evaluation. 1932–1938.3 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
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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.