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.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 Cristina Bosco
Since
Specialization
Citations
This map shows the geographic impact of Cristina Bosco'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 Cristina Bosco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cristina Bosco more than expected).
This network shows the impact of papers produced by Cristina Bosco. 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 Cristina Bosco. The network helps show where Cristina Bosco may publish in the future.
Co-authorship network of co-authors of Cristina Bosco
This figure shows the co-authorship network connecting the top 25 collaborators of Cristina Bosco.
A scholar is included among the top collaborators of Cristina Bosco 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 Cristina Bosco. Cristina Bosco is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lai, Mirko, Marco Antonio Stranisci, Cristina Bosco, Rossana Damiano, & Viviana Patti. (2021). HaMor at the Profiling Hate Speech Spreaders on Twitter. Institutional Research Information System University of Turin (University of Turin). 2936. 2047–2055.1 indexed citations
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, 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
9.
Sanguinetti, Manuela, et al.. (2018). PoSTWITA-UD: an Italian Twitter Treebank in Universal Dependencies.. Language Resources and Evaluation. 1768–1775.31 indexed citations
Stranisci, Marco Antonio, Cristina Bosco, Delia Irazú Hernández Farías, & Viviana Patti. (2016). Annotating Sentiment and Irony in the Online Italian Political Debate on #labuonascuola.. Language Resources and Evaluation. 2892–2899.15 indexed citations
12.
Bosco, Cristina, et al.. (2016). Tweeting and being ironic in the debate about a political reform: the French annotated corpus TWitter-MariagePourTous. Language Resources and Evaluation. 1619–1626.6 indexed citations
13.
Bosco, Cristina, et al.. (2015). Developing corpora for sentiment analysis: the case of irony and senti-TUT. International Conference on Artificial Intelligence. 4158–4162.6 indexed citations
14.
Bosco, Cristina, et al.. (2015). Developing Corpora for Sentiment Analysis: The Case of Irony and Senti-TUT (Extended Abstract). Institutional Research Information System University of Turin (University of Turin). 4158–4162.5 indexed citations
15.
Bosco, Cristina, Simonetta Montemagni⋄, & Maria Simi. (2013). Converting Italian Treebanks: Towards an Italian Stanford Dependency Treebank. 1. 61–69.29 indexed citations
16.
Bosco, Cristina, et al.. (2012). A treebank-based study on the influence of Italian word order on parsing performance. Language Resources and Evaluation. 1985–1992.6 indexed citations
17.
Bosco, Cristina, Manuela Sanguinetti, & Leonardo Lesmo. (2012). The Parallel-TUT: a multilingual and multiformat treebank. Language Resources and Evaluation. 1932–1938.3 indexed citations
18.
Magnini, Bernardo, Fabio Tamburini, Cristina Bosco, et al.. (2008). Evaluation of Natural Language Tools for Italian: EVALITA 2007. Language Resources and Evaluation. 2536–2543.10 indexed citations
19.
Bosco, Cristina, et al.. (2000). Building a Treebank for Italian: a Data-driven Annotation Schema. Language Resources and Evaluation. 99–105.58 indexed citations
20.
Bosco, Cristina. (1998). Teresa, mujer y ruin. Dialnet (Universidad de la Rioja). 14. 191–191.
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.