Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Building and evaluating resources for sentiment analysis in the Greek language

Tools
- Tools
+ Tools

Tsakalidis, Adam, Papadopoulos, Symeon, Voskaki, Rania, Ioannidou, Kyriaki, Boididou, Christina, Cristea, Alexandra I., Liakata, Maria and Kompatsiaris, Yiannis (2018) Building and evaluating resources for sentiment analysis in the Greek language. Language Resources and Evaluation, 52 . pp. 1021-1044. doi:10.1007/s10579-018-9420-4 ISSN 1574-020X.

[img]
Preview
PDF
WRAP-building-evaluating-resources-Tsakalidis-2018.pdf - Published Version - Requires a PDF viewer.
Available under License Creative Commons Attribution 4.0.

Download (716Kb) | Preview
Official URL: http://dx.doi.org/10.1007/s10579-018-9420-4

Request Changes to record.

Abstract

Sentiment lexicons and word embeddings constitute well-established sources of information for sentiment analysis in online social media. Although their effectiveness has been demonstrated in state-of-the-art sentiment analysis and related tasks in the English language, such publicly available resources are much less developed and evaluated for the Greek language. In this paper, we tackle the problems arising when analyzing text in such an under-resourced language. We present and make publicly available a rich set of such resources, ranging from a manually annotated lexicon, to semi-supervised word embedding vectors and annotated datasets for different tasks. Our experiments using different algorithms and parameters on our resources show promising results over standard baselines; on average, we achieve a 24.9% relative improvement in F-score on the cross-domain sentiment analysis task when training the same algorithms with our resources, compared to training them on more traditional feature sources, such as n-grams. Importantly, while our resources were built with the primary focus on the cross-domain sentiment analysis task, they also show promising results in related tasks, such as emotion analysis and sarcasm detection.

Item Type: Journal Article
Subjects: H Social Sciences > HM Sociology
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH): Online social networks -- Greece, Greek language, Twitter (Firm)
Journal or Publication Title: Language Resources and Evaluation
Publisher: Springer
ISSN: 1574-020X
Official Date: December 2018
Dates:
DateEvent
December 2018Published
14 July 2018Available
Volume: 52
Page Range: pp. 1021-1044
DOI: 10.1007/s10579-018-9420-4
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 17 September 2018
Date of first compliant Open Access: 18 September 2018
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EP/N510129/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
EP/L016400/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
UNSPECIFIEDAlan Turing Institutehttp://dx.doi.org/10.13039/100012338

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us