Dialogue Evaluation 2023
RuSentNE
Sentiment Analysis for Named Entities in News Texts
The shared task is over. Thank you all for participating!
Participants may submit a paper for publication in the Conference Proceedings "Computational Linguistics and Intellectual Technologies" with a description of the solution and analysis of the results. Deadline for submission of Dialogue Evaluation articles: 8 April 11:59 pm. Please read the publishing rules for the Dialogue Evaluation track.
Links
Key dates
- 26 December — publication of the train data;
- 4 March — publication of the test data;
- 10 March — submission of the results;
- 13 March — results of the competition;
- 8 April — paper submission deadline.
Description
Sentiment analysis, i.e. identification of opinions on the subject discussed in the text, is one of the most actively developing applications of natural language processing.
Sentiment analysis of news texts is an important direction in the field of opinion analysis, since the detection and tracking of sentiment trends in the news flow is important for building various kinds of analytical systems, tracking the image in the media of specific people or companies.
Sentiment in relation to entity in a news text can come from at least three different sources:
- opinion of the author of the text,
- cited opinion, while the carrier of the opinion may or may not be mentioned in the text,
- an implicit opinion that follows from any of the actions or reactions mentioned, for example, X fired Y.. Such information is often present even in an apparently neutral account of events.
Task
We invite participants to solve the problem of extracting sentiments of three classes (negative, positive, neutral) from news texts in relation to pre-marked entities such as PERSON, ORGANIZATION, PROFESSION, COUNTRY, NATIONALITY within a separate sentence.