In the mood the dynamics of collective sentiments on Twitter

dc.contributor.author	Charlton, Nathaniel	en_US
dc.date.accessioned	2016-07-04T03:49:06Z
dc.date.available	2016-07-04T03:49:06Z
dc.date.issued	2016	en_US
dc.identifier.other	HPU4160397	en_US
dc.identifier.uri	https://lib.hpu.edu.vn/handle/123456789/21915	en_US
dc.description.abstract	We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SENTISTRENGTH program. Specifically we make three contributions. Firstly, we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user.	en_US
dc.format.extent	28 p.	en_US
dc.format.mimetype	application/pdf	en_US
dc.language.iso	en	en_US
dc.subject	Mathematics	en_US
dc.subject	Mathematical modelling	en_US
dc.subject	Computer	en_US
dc.subject	Simulation	en_US
dc.subject	Evolving networks	en_US
dc.subject	Twitter communities	en_US
dc.subject	Dynamics of collective emotions	en_US
dc.subject	Communicability	en_US
dc.title	In the mood the dynamics of collective sentiments on Twitter	en_US
dc.type	Article	en_US
dc.size	1.99MB	en_US
dc.department	Education	en_US