Zobrazeno 1 - 6
of 6
pro vyhledávání: '"social media, natural language processing"'
Autor:
Mason, Matt, Rowe, Francisco
There is a growing academic literature examining anti-immigration sentiment posted onto social media platforms, with evidence emerging of its impact on rises in “real physical” incidents of hate. Despite this, little is understood about the spati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::170fd18cc20a85ce6a85e709420c5765
Background: Social media discussions around medication use by clinicians and patients have created a public record that can provide new, timely insights into various unique and existing topics, including adverse events. Unstructured patient discussio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66b23a648c45b9a2806636b2a460ee98
Publikováno v:
Volume: 27, Issue: 3 1780-1793
Turkish Journal of Electrical Engineering and Computer Science
Turkish Journal of Electrical Engineering and Computer Science
This paper presents a hybrid methodology for Turkish sentiment analysis, which combines the lexicon-based and machine learning (ML)-based approaches. On the lexicon-based side, we use a sentiment dictionary that is extended with a synonyms lexicon. B
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::259abe7b204ec886df9cc223512882ff
https://doi.org/10.3906/elk-1808-189
https://doi.org/10.3906/elk-1808-189
Publikováno v:
Encyclopedia of Social Network Analysis and Mining ISBN: 9781461471639
Encyclopedia of Social Network Analysis and Mining. 2nd Ed.
Encyclopedia of Social Network Analysis and Mining. 2nd Ed.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0debb777631164c8e38f9ed641e48892
http://hdl.handle.net/2318/1652672
http://hdl.handle.net/2318/1652672
Autor:
Aaron Nojima, Ruchit Nagar, Clark C. Freifeld, Rumi Chunara, John S. Brownstein, Qingyu Yuan, Mauricio Santillana
Publikováno v:
Journal of Medical Internet Research, Vol 16, Iss 10, p e236 (2014)
Journal of Medical Internet Research
Journal of Medical Internet Research
Background: Twitter has shown some usefulness in predicting influenza cases on a weekly basis in multiple countries and on different geographic scales. Recently, Broniatowski and colleagues suggested Twitter’s relevance at the city-level for New Yo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1241b6440895247b2b297047781c31e
http://www.jmir.org/2014/10/e236/
http://www.jmir.org/2014/10/e236/
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