NewSoMe Corpus of Opinion in News Reports
Item Name: | NewSoMe Corpus of Opinion in News Reports |
Author(s): | Roser Sauri, Judith Domingo, Toni Badia |
LDC Catalog No.: | LDC2015T17 |
ISBN: | 1-58563-731-9 |
ISLRN: | 793-803-205-712-6 |
DOI: | https://doi.org/10.35111/y013-n255 |
Release Date: | September 15, 2015 |
Member Year(s): | 2015 |
DCMI Type(s): | Text |
Data Source(s): | newswire, web collection |
Application(s): | discourse analysis, information extraction |
Language(s): | Spanish, Catalan, Portuguese |
Language ID(s): | spa, cat, por |
License(s): |
LDC User Agreement for Non-Members |
Online Documentation: | LDC2015T17 Documents |
Licensing Instructions: | Subscription & Standard Members, and Non-Members |
Citation: | Sauri, Roser, Judith Domingo, and Toni Badia. NewSoMe Corpus of Opinion in News Reports LDC2015T17. Web Download. Philadelphia: Linguistic Data Consortium, 2015. |
Related Works: | View |
Introduction
NewSoMe Corpus of Opinion in News Reports was compiled at Barcelona Media and consists of Spanish, Catalan and Portuguese news reports annotated for opinions. It is part of the NewSoMe (News and Social Media) set of corpora presenting opinion annotations across several genres and covering multiple languages. NewSoMe is the result of an effort to build a unifying annotation framework for analyzing opinion in different genres, ranging from controlled text, such as news reports, to diverse types of user-generated content that includes blogs, product reviews and microblogs.
Data
The source data in this release was obtained from various newspaper websites and consists of approximately 200 documents in each of Spanish, Catalan and Portuguese. The annotation was carried out manually through the crowdsourcing platform CrowdFlower with seven annotations per layer that were aggregated for this data set. The layers annotated were topic, segment, cue, subjectivity, polarity and intensity.
Data is presented as UTF-8 either as plain text or in CSV files.
Samples
Please view the following samples.
Updates
None at this time.