RT Journal Article
T1 Differentiating users by language and location estimation in sentiment analisys of informal text during major public events
A1 Fernández Gavilanes, Milagros
A1 Juncal Martínez, Jonathan
A1 García Méndez, Silvia
A1 Costa Montenegro, Enrique
A1 González Castaño, Francisco Javier
K1 6308 Comunicaciones Sociales
K1 6309 Grupos Sociales
AB In recent years there has been intense work on the analysis of social media to support marketing campaigns. A proper methodology for sentiment analysis is a crucial asset in this regard. However, when monitoring major public events the behaviour or social media users may be strongly biased by punctual actions of the participating characters and the sense of group belonging, which is typically linked to specific geographical areas. In this paper, we present a solution combining a location prediction methodology with an unsupervised technique for sentiment analysis to assess automatically the engagement of social network users in different countries during an event with worldwide impact. As far as the authors know, this is the first time such techniques are jointly considered. We demonstrate that the technique is coherent with the intrinsic disposition of individual users to typical actions of the characters participating in the events, as well as with the sense of group belonging.
PB Expert Systems with Applications
SN 09574174
YR 2019
FD 2019-03-01
LK http://hdl.handle.net/11093/6811
UL http://hdl.handle.net/11093/6811
LA eng
NO Expert Systems with Applications, 117, 15-28 (2019)
NO Ministerio de Economía, Industria y Competitividad | Ref. TEC2016-76465-C2-2-R
DS Investigo
RD 11-dic-2024