Authority-Based Conversation Tracking in Twitter: An Unattended Methodological Approach
Twitter is undoubtedly one of the most widely used data sources to analyze human communication. The literature is full of examples where Twitter is accessed, and data are downloaded as the previous step to a more in-depth analysis in a wide variety of knowledge areas. Unfortunately, the extraction o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/9/3273 |
| _version_ | 1797568529635999744 |
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| author | Marçal Mora-Cantallops Salvador Sánchez-Alonso Elena García-Barriocanal Miguel-Ángel Sicilia |
| author_facet | Marçal Mora-Cantallops Salvador Sánchez-Alonso Elena García-Barriocanal Miguel-Ángel Sicilia |
| author_sort | Marçal Mora-Cantallops |
| collection | DOAJ |
| description | Twitter is undoubtedly one of the most widely used data sources to analyze human communication. The literature is full of examples where Twitter is accessed, and data are downloaded as the previous step to a more in-depth analysis in a wide variety of knowledge areas. Unfortunately, the extraction of relevant information from the opinions that users freely express in Twitter is complicated, both because of the volume generated—more than 6000 tweets per second—and the difficulties related to filtering out only what is pertinent to our research. Inspired by the fact that a large part of users use Twitter to communicate or receive political information, we created a method that allows for the monitoring of a set of users (which we will call authorities) and the tracking of the information published by them about an event. Our approach consists of dynamically and automatically monitoring the hottest topics among all the conversations where the authorities are involved, and retrieving the tweets in connection with those topics, filtering other conversations out. Although our case study involves the method being applied to the political discussions held during the Spanish general, local, and European elections of April/May 2019, the method is equally applicable to many other contexts, such as sporting events, marketing campaigns, or health crises. |
| first_indexed | 2024-03-10T19:58:15Z |
| format | Article |
| id | doaj.art-39b8a3a89765482c8bc46c0960a948d1 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T19:58:15Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-39b8a3a89765482c8bc46c0960a948d12023-11-19T23:46:43ZengMDPI AGApplied Sciences2076-34172020-05-01109327310.3390/app10093273Authority-Based Conversation Tracking in Twitter: An Unattended Methodological ApproachMarçal Mora-Cantallops0Salvador Sánchez-Alonso1Elena García-Barriocanal2Miguel-Ángel Sicilia3Computer Science Department, Universidad de Alcalá, 28801 Alcalá de Henares, Madrid, SpainComputer Science Department, Universidad de Alcalá, 28801 Alcalá de Henares, Madrid, SpainComputer Science Department, Universidad de Alcalá, 28801 Alcalá de Henares, Madrid, SpainComputer Science Department, Universidad de Alcalá, 28801 Alcalá de Henares, Madrid, SpainTwitter is undoubtedly one of the most widely used data sources to analyze human communication. The literature is full of examples where Twitter is accessed, and data are downloaded as the previous step to a more in-depth analysis in a wide variety of knowledge areas. Unfortunately, the extraction of relevant information from the opinions that users freely express in Twitter is complicated, both because of the volume generated—more than 6000 tweets per second—and the difficulties related to filtering out only what is pertinent to our research. Inspired by the fact that a large part of users use Twitter to communicate or receive political information, we created a method that allows for the monitoring of a set of users (which we will call authorities) and the tracking of the information published by them about an event. Our approach consists of dynamically and automatically monitoring the hottest topics among all the conversations where the authorities are involved, and retrieving the tweets in connection with those topics, filtering other conversations out. Although our case study involves the method being applied to the political discussions held during the Spanish general, local, and European elections of April/May 2019, the method is equally applicable to many other contexts, such as sporting events, marketing campaigns, or health crises.https://www.mdpi.com/2076-3417/10/9/3273Twittertopic trackingdata extractioninformation retrievaldata mining |
| spellingShingle | Marçal Mora-Cantallops Salvador Sánchez-Alonso Elena García-Barriocanal Miguel-Ángel Sicilia Authority-Based Conversation Tracking in Twitter: An Unattended Methodological Approach Applied Sciences topic tracking data extraction information retrieval data mining |
| title | Authority-Based Conversation Tracking in Twitter: An Unattended Methodological Approach |
| title_full | Authority-Based Conversation Tracking in Twitter: An Unattended Methodological Approach |
| title_fullStr | Authority-Based Conversation Tracking in Twitter: An Unattended Methodological Approach |
| title_full_unstemmed | Authority-Based Conversation Tracking in Twitter: An Unattended Methodological Approach |
| title_short | Authority-Based Conversation Tracking in Twitter: An Unattended Methodological Approach |
| title_sort | authority based conversation tracking in twitter an unattended methodological approach |
| topic | Twitter topic tracking data extraction information retrieval data mining |
| url | https://www.mdpi.com/2076-3417/10/9/3273 |
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