P
Preslav Nakov
Researcher at Qatar Computing Research Institute
Publications - 387
Citations - 17729
Preslav Nakov is an academic researcher from Qatar Computing Research Institute. The author has contributed to research in topics: Machine translation & Task (project management). The author has an hindex of 61, co-authored 387 publications receiving 14335 citations. Previous affiliations of Preslav Nakov include Khalifa University & University of California, Berkeley.
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Proceedings ArticleDOI
SemEval-2017 Task 4: Sentiment Analysis in Twitter
TL;DR: Crowdourcing on Amazon Mechanical Turk was used to label a large Twitter training dataset along with additional test sets of Twitter and SMS messages for both subtasks, which included two subtasks: A, an expression-level subtask, and B, a message level subtask.
Proceedings ArticleDOI
SemEval-2016 Task 4: Sentiment Analysis in Twitter
TL;DR: The SemEval-2016 Task 4 comprises five subtasks, three of which represent a significant departure from previous editions. as mentioned in this paper discusses the fourth year of the Sentiment Analysis in Twitter Task and discusses the three new subtasks focus on two variants of the basic sentiment classification in Twitter task.
Proceedings Article
SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations between Pairs of Nominals
Iris Hendrickx,Su Nam Kim,Zornitsa Kozareva,Preslav Nakov,Diarmuid Ó Séaghdha,Sebastian Padó,Marco Pennacchiotti,Lorenza Romano,Stan Szpakowicz +8 more
TL;DR: This paper defines the task, describes the training and test data and the process of their creation, lists the participating systems (10 teams, 28 runs), and discusses their results.
Proceedings ArticleDOI
Predicting the Type and Target of Offensive Posts in Social Media
TL;DR: The Offensive Language Identification Dataset (OLID), a new dataset with tweets annotated for offensive content using a fine-grained three-layer annotation scheme, is complied and made publicly available.
Proceedings ArticleDOI
SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval).
TL;DR: The SemEval-2019 Task 6 on Identifying and categorizing Offensive Language in Social Media (OffensEval) as mentioned in this paper was based on a new dataset, the Offensive Language Identification Dataset (OLID), which contains over 14,000 English tweets, and featured three sub-tasks.