Abstract
Social media have played a relevant role in facilitating communication and coordination among people. Digital traces generated by users in social media sites provides a promising source of data for use in different contexts. The avast amount of data contains information not only about the content of the message but also about who generated the information and to whom it was directed, the instant of time it was published, or the location of the user at the time of publication. Thanks to all this meta-information, the study of users’ actions can be analyzed at different levels of detail and taking into account different perspectives.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Del Val, E., Rebollo, M., Botti, V.: Does the type of event influence how user interactions evolve on Twitter? PLOS ONE 10(5), 1–32 (2015)
Del Val, E., Palanca, J., Rebollo, M.: U-Tool: A urban-toolkit for enhancing city maps through citizens activity. In: 14th PAAMS, pp. 243–246 (2016)
Del Val, E., Martínez, C., Botti, V.: Analyzing users activity in online social networks over time through a multi-agent framework. Soft Comput. 20, 4331–4345 (2016)
Del Val, E., Martínez, C., Botti, V.: A multi-agent framework for the analysis of users behavior over time in on-line social networks. In: Proceedings of SOCO, pp. 191–201 (2015)
Grabowicz, P.A., Ramasco, J.J., Gonçalves, B., Eguíluz, V.M.: Entangling mobility and interactions in social media. PloS ONE 9(3), e92196 (2014)
Gryc, W., Moilanen, K.: Leveraging textual sentiment analysis with social network modelling. In: From Text to Political Positions: Text Analysis Across Disciplines, vol. 55, p. 47 (2014)
West, R., Paskov, H.S., Leskovec, J., Potts, C.: Exploiting social network structure for person-to-person sentiment analysis. arXiv preprint arXiv:1409.2450
Caragea, C., Squicciarini, A., Stehle, S., Neppalli, K., Tapia, A.: Mapping moods: Geo-mapped sentiment analysis during hurricane sandy. In: Proceedings of ISCRAM
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Vivanco, E., Palanca, J., del Val, E., Rebollo, M., Botti, V. (2017). Using Geo-Tagged Sentiment to Better Understand Social Interactions. In: Demazeau, Y., Davidsson, P., Bajo, J., Vale, Z. (eds) Advances in Practical Applications of Cyber-Physical Multi-Agent Systems: The PAAMS Collection. PAAMS 2017. Lecture Notes in Computer Science(), vol 10349. Springer, Cham. https://doi.org/10.1007/978-3-319-59930-4_40
Download citation
DOI: https://doi.org/10.1007/978-3-319-59930-4_40
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-59929-8
Online ISBN: 978-3-319-59930-4
eBook Packages: Computer ScienceComputer Science (R0)