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- Publisher Website: 10.1007/978-3-319-20367-6_18
- Scopus: eid_2-s2.0-84950321054
- WOS: WOS:000364813200018
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Conference Paper: Hashtag popularity on twitter: Analyzing co-occurrence of multiple Hashtags
Title | Hashtag popularity on twitter: Analyzing co-occurrence of multiple Hashtags |
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Authors | |
Keywords | Twitter Hashtag Hashtag co-occurrence Metacognitive experience |
Issue Date | 2015 |
Citation | International Conference on Social Computing and Social Media, Los Angeles, CA, 2-7 August 2015. In Lecture Notes in Computer Science, 2015, v. 9182, p. 169-182 How to Cite? |
Abstract | © Springer International Publishing Switzerland 2015. Hashtags increase the reachability of a tweet to manifolds and consequently, has the potential to create a wider market for brands. The frequent use of a hashtag features it in the Twitter trending list. In this study we want to understand what contributes to the popularity of a hashtag. Further, hashtags generally come in groups in a tweet. In fact, an investigation on a real world dataset of Great Eastern Japan Earthquake reveals that 50% of hashtags appear in a tweet with at least another hashtag. How this co-occurrence of hashtags affects its popularity is also not addressed heretofore, which is the focus herein. Results indicate that if a hashtag appears with one or more other similar hashtags, popularity of the hashtag increases. In contrast, if a hashtag appears with dissimilar hashtags, popularity of the focal hashtag decreases. The results reverse when dissimilar hashtags come along with a URL. |
Persistent Identifier | http://hdl.handle.net/10722/277027 |
ISSN | 2023 SCImago Journal Rankings: 0.606 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Pervin, Nargis | - |
dc.contributor.author | Phan, Tuan Quang | - |
dc.contributor.author | Datta, Anindya | - |
dc.contributor.author | Takeda, Hideaki | - |
dc.contributor.author | Toriumi, Fujio | - |
dc.date.accessioned | 2019-09-18T08:35:23Z | - |
dc.date.available | 2019-09-18T08:35:23Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | International Conference on Social Computing and Social Media, Los Angeles, CA, 2-7 August 2015. In Lecture Notes in Computer Science, 2015, v. 9182, p. 169-182 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | http://hdl.handle.net/10722/277027 | - |
dc.description.abstract | © Springer International Publishing Switzerland 2015. Hashtags increase the reachability of a tweet to manifolds and consequently, has the potential to create a wider market for brands. The frequent use of a hashtag features it in the Twitter trending list. In this study we want to understand what contributes to the popularity of a hashtag. Further, hashtags generally come in groups in a tweet. In fact, an investigation on a real world dataset of Great Eastern Japan Earthquake reveals that 50% of hashtags appear in a tweet with at least another hashtag. How this co-occurrence of hashtags affects its popularity is also not addressed heretofore, which is the focus herein. Results indicate that if a hashtag appears with one or more other similar hashtags, popularity of the hashtag increases. In contrast, if a hashtag appears with dissimilar hashtags, popularity of the focal hashtag decreases. The results reverse when dissimilar hashtags come along with a URL. | - |
dc.language | eng | - |
dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.subject | - | |
dc.subject | Hashtag | - |
dc.subject | Hashtag co-occurrence | - |
dc.subject | Metacognitive experience | - |
dc.title | Hashtag popularity on twitter: Analyzing co-occurrence of multiple Hashtags | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/978-3-319-20367-6_18 | - |
dc.identifier.scopus | eid_2-s2.0-84950321054 | - |
dc.identifier.volume | 9182 | - |
dc.identifier.spage | 169 | - |
dc.identifier.epage | 182 | - |
dc.identifier.eissn | 1611-3349 | - |
dc.identifier.isi | WOS:000364813200018 | - |
dc.identifier.issnl | 0302-9743 | - |