Analysis of Selected Twitter Headers During the Pandemic Using Big Data Method
| dc.contributor.author | Acar İ.A. | |
| dc.contributor.author | Altıntaş V. | |
| dc.date.accessioned | 2024-07-22T08:05:11Z | |
| dc.date.available | 2024-07-22T08:05:11Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | The behaviours and shares of social media users have recently been closely followed by governments, institutions and companies. Governments/companies determine some of their strategies by processing the “big data” created by the shares made by users. Big data analysis has been used extensively lately. During the pandemic period, people shared their ideas and experiences on social media platforms. Twitter is one of the most popular worldwide Online Social Network (OSN). One of these sharing platforms is Twitter Social Media Platform. In this study, between 1 and 31 May 2020, user posts containing keywords related to COVID-19 were collected. The analysis of the shares was made using natural language processing and text mining techniques on the corpus. In this paper, we use topic identification and sentiment analysis to explore a large number of tweets in Turkey. We investigate 19.199.490 tweets in Turkish, and we analyse comparing the effectiveness of topic identification and sentiment analysis in the messages in pandemic days. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. | |
| dc.identifier.DOI-ID | 10.1007/978-981-16-8024-3_13 | |
| dc.identifier.issn | 25097873 | |
| dc.identifier.uri | http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/13034 | |
| dc.language.iso | English | |
| dc.publisher | Springer Nature | |
| dc.title | Analysis of Selected Twitter Headers During the Pandemic Using Big Data Method | |
| dc.type | Book chapter |