Real-Time Twitter Data Analysis: A Survey
Internet users are used to a steady stream of facts in the contemporary world. Numerous social media platforms, including Twitter, Facebook, and Quora, are plagued with spam accounts, posing a significant problem. These accounts are created to trick unwary real users into clicking on dangerous links...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Human Development
2022-12-01
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| Series: | UHD Journal of Science and Technology |
| Subjects: | |
| Online Access: | https://journals.uhd.edu.iq/index.php/uhdjst/article/view/995 |
| _version_ | 1797958292299841536 |
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| author | Hakar Mohammed Rasul Alaa Khalil Jumaa |
| author_facet | Hakar Mohammed Rasul Alaa Khalil Jumaa |
| author_sort | Hakar Mohammed Rasul |
| collection | DOAJ |
| description | Internet users are used to a steady stream of facts in the contemporary world. Numerous social media platforms, including Twitter, Facebook, and Quora, are plagued with spam accounts, posing a significant problem. These accounts are created to trick unwary real users into clicking on dangerous links or to continue publishing repetitious messages using automated software. This may significantly affect the user experiences on these websites. Effective methods for detecting certain types of spam have been intensively researched and developed. Effectively resolving this issue might be aided by doing sentiment analysis on these postings. Hence, this research provides a background study on Twitter data analysis, and surveys existing papers on Twitter sentiment analysis and fake account detection and classification. The investigation is restricted to the identification of social bots on the Twitter social media network. It examines the methodologies, classifiers, and detection accuracies of the several detection strategies now in use. |
| first_indexed | 2024-04-11T00:17:57Z |
| format | Article |
| id | doaj.art-cf39907c7af24223870f7f0a651be66f |
| institution | Directory Open Access Journal |
| issn | 2521-4209 2521-4217 |
| language | English |
| last_indexed | 2024-04-11T00:17:57Z |
| publishDate | 2022-12-01 |
| publisher | University of Human Development |
| record_format | Article |
| series | UHD Journal of Science and Technology |
| spelling | doaj.art-cf39907c7af24223870f7f0a651be66f2023-01-08T19:42:54ZengUniversity of Human DevelopmentUHD Journal of Science and Technology2521-42092521-42172022-12-016214715510.21928/uhdjst.v6n2y2022.pp147-1551126Real-Time Twitter Data Analysis: A SurveyHakar Mohammed Rasul0Alaa Khalil Jumaa1Technical college of Informatics, Sulaimani Polytechnic University, Sulaimani 46001, Kurdistan Region, IraqTechnical college of Informatics, Sulaimani Polytechnic University, Sulaimani 46001, Kurdistan Region, IraqInternet users are used to a steady stream of facts in the contemporary world. Numerous social media platforms, including Twitter, Facebook, and Quora, are plagued with spam accounts, posing a significant problem. These accounts are created to trick unwary real users into clicking on dangerous links or to continue publishing repetitious messages using automated software. This may significantly affect the user experiences on these websites. Effective methods for detecting certain types of spam have been intensively researched and developed. Effectively resolving this issue might be aided by doing sentiment analysis on these postings. Hence, this research provides a background study on Twitter data analysis, and surveys existing papers on Twitter sentiment analysis and fake account detection and classification. The investigation is restricted to the identification of social bots on the Twitter social media network. It examines the methodologies, classifiers, and detection accuracies of the several detection strategies now in use.https://journals.uhd.edu.iq/index.php/uhdjst/article/view/995twitterdata analysistwitter streaming application programming interfacesentiment analysisbot detection |
| spellingShingle | Hakar Mohammed Rasul Alaa Khalil Jumaa Real-Time Twitter Data Analysis: A Survey UHD Journal of Science and Technology data analysis twitter streaming application programming interface sentiment analysis bot detection |
| title | Real-Time Twitter Data Analysis: A Survey |
| title_full | Real-Time Twitter Data Analysis: A Survey |
| title_fullStr | Real-Time Twitter Data Analysis: A Survey |
| title_full_unstemmed | Real-Time Twitter Data Analysis: A Survey |
| title_short | Real-Time Twitter Data Analysis: A Survey |
| title_sort | real time twitter data analysis a survey |
| topic | twitter data analysis twitter streaming application programming interface sentiment analysis bot detection |
| url | https://journals.uhd.edu.iq/index.php/uhdjst/article/view/995 |
| work_keys_str_mv | AT hakarmohammedrasul realtimetwitterdataanalysisasurvey AT alaakhaliljumaa realtimetwitterdataanalysisasurvey |