Full text
Preview |
PDF
- Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (166kB) | Preview |
Sentiment analysis for social media
Citation
Iglesias Fernández, Carlos Ángel 
ORCID: https://orcid.org/0000-0002-1755-2712 and Moreno, Antonio
(2019).
Sentiment analysis for social media.
"Applied Sciences-Basel", v. 9
(n. 5037);
pp. 1-4.
ISSN 2076-3417.
https://doi.org/10.3390/app9235037.
Description
| Title: | Sentiment analysis for social media |
|---|---|
| Author/s: |
|
| Item Type: | Article |
| Título de Revista/Publicación: | Applied Sciences-Basel |
| Date: | 22 November 2019 |
| ISSN: | 2076-3417 |
| Volume: | 9 |
| Subjects: | |
| Freetext Keywords: | sentiment analysis; emotion analysis; social media; affect computing |
| Faculty: | E.T.S.I. Telecomunicación (UPM) |
| Department: | Ingeniería de Sistemas Telemáticos |
| Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
Abstract
Sentiment analysis has become a key technology to gain insight from social networks. The field has reached a level of maturity that paves the way for its exploitation in many different fields such as marketing, health, banking or politics. The latest technological advancements, such as deep learning techniques, have solved some of the traditional challenges in the area caused by the scarcity of lexical resources. In this Special Issue, different approaches that advance this discipline are presented. The contributed articles belong to two broad groups: technological contributions and applications.
More information
| Item ID: | 63862 |
|---|---|
| DC Identifier: | https://oa.upm.es/63862/ |
| OAI Identifier: | oai:oa.upm.es:63862 |
| DOI: | 10.3390/app9235037 |
| Official URL: | https://www.mdpi.com/2076-3417/9/23/5037 |
| Deposited by: | Memoria Investigacion |
| Deposited on: | 29 Sep 2020 15:33 |
| Last Modified: | 01 Apr 2023 10:14 |
