Sentiment Analysis for the Social Media: a Case Study for Turkish General Elections
| dc.contributor.author | Yumusak, Semih | |
| dc.contributor.author | Oztoprak, Kasim | |
| dc.contributor.author | Dogdu, Erdogan | |
| dc.contributor.author | Uysal, Elif | |
| dc.contributor.other | 06.01. Bilgisayar Mühendisliği | |
| dc.contributor.other | 06. Mühendislik Fakültesi | |
| dc.contributor.other | 01. Çankaya Üniversitesi | |
| dc.date.accessioned | 2024-03-28T12:20:43Z | |
| dc.date.accessioned | 2025-09-18T12:49:30Z | |
| dc.date.available | 2024-03-28T12:20:43Z | |
| dc.date.available | 2025-09-18T12:49:30Z | |
| dc.date.issued | 2017 | |
| dc.description | Uysal, Elif/0000-0002-7258-4872; Dogdu, Erdogan/0000-0001-5987-0164; Yumusak, Semih/0000-0002-8878-4991 | en_US |
| dc.description.abstract | The ideas expressed in social media are not always compliant with natural language rules, and the mood and emotion indicators are mostly highlighted by emoticons and emotion specific keywords. There are language independent emotion keywords (e.g. love, hate, good, bad), besides every language has its own particular emotion specific keywords. These keywords can be used for polarity analysis for a particular sentence. In this study, we first created a Turkish dictionary containing emotion specific keywords. Then, we used this dictionary to detect the polarity of tweets that are collected by querying political keywords right before the Turkish general election in 2015. The tweets were collected based on their relatedness with three main categories: the political leaders, ideologies, and political parties. The polarity of these tweets are analyzed in comparison with the election results. | en_US |
| dc.identifier.citation | Uysal, Elif...et al. "Sentiment Analysis for the Social Media: A Case Study for Turkish General Elections", ACM SE '17: Proceedings of the SouthEast Conference, April 2017, pp. 215-218. | en_US |
| dc.identifier.doi | 10.1145/3077286.3077569 | |
| dc.identifier.isbn | 9781450350242 | |
| dc.identifier.scopus | 2-s2.0-85021419464 | |
| dc.identifier.uri | https://doi.org/10.1145/3077286.3077569 | |
| dc.identifier.uri | https://hdl.handle.net/123456789/12372 | |
| dc.language.iso | en | en_US |
| dc.publisher | Assoc Computing Machinery | en_US |
| dc.relation.ispartof | ACM Southeast Regional Conference -- APR 13-17, 2017 -- Kennesaw, GA | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Social Media | en_US |
| dc.subject | Sentiment Analysis | en_US |
| dc.subject | Political Tweets | en_US |
| dc.title | Sentiment Analysis for the Social Media: a Case Study for Turkish General Elections | en_US |
| dc.title | Sentiment Analysis for the Social Media: A Case Study for Turkish General Elections | tr_TR |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
| gdc.author.id | Uysal, Elif/0000-0002-7258-4872 | |
| gdc.author.id | Dogdu, Erdogan/0000-0001-5987-0164 | |
| gdc.author.id | Yumusak, Semih/0000-0002-8878-4991 | |
| gdc.author.institutional | Doğdu, Erdoğan | |
| gdc.author.scopusid | 58656986000 | |
| gdc.author.scopusid | 56814988500 | |
| gdc.author.scopusid | 21743623400 | |
| gdc.author.scopusid | 6603501593 | |
| gdc.author.wosid | Oztoprak, Kasim/U-1631-2018 | |
| gdc.author.wosid | Uysal, Elif/Aaf-7958-2019 | |
| gdc.author.wosid | Yumusak, Semih/Glt-8323-2022 | |
| gdc.description.department | Çankaya University | en_US |
| gdc.description.departmenttemp | [Uysal, Elif; Yumusak, Semih; Oztoprak, Kasim] KTO Karatay Univ, Konya, Turkey; [Dogdu, Erdogan] Cankaya Univ, Georgia State Univ Adjunct, Ankara, Turkey | en_US |
| gdc.description.endpage | 218 | en_US |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| gdc.description.startpage | 215 | en_US |
| gdc.description.woscitationindex | Conference Proceedings Citation Index - Science | |
| gdc.identifier.openalex | W2612739139 | |
| gdc.identifier.wos | WOS:000945372900040 | |
| gdc.openalex.fwci | 1.8334371 | |
| gdc.openalex.normalizedpercentile | 0.87 | |
| gdc.opencitations.count | 10 | |
| gdc.plumx.crossrefcites | 10 | |
| gdc.plumx.mendeley | 36 | |
| gdc.plumx.scopuscites | 11 | |
| gdc.scopus.citedcount | 11 | |
| gdc.wos.citedcount | 8 | |
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