Text mining and analytics a case study from news channels posts on Facebook
Nowadays, social media has swiftly altered the media landscape resulting in a competitive environment of news creation and dissemination. Sharing news through social media websites is almost provided in a textual format. The nature of the disseminated text is considered as unstructured text. Text mi...
| Main Authors: | , , |
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| Format: | Book Chapter |
| Language: | English |
| Published: |
Springer
2017
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/21628/1/5.%20Text%20Mining%20and%20Analytics%20A%20Case%20Study%20from%20News%20Channels%20Posts%20on%20Facebook.pdf |
| _version_ | 1796992797458300928 |
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| author | Chaker, Mhamdi Al-Emran, Mostafa Salloum, Said A. |
| author_facet | Chaker, Mhamdi Al-Emran, Mostafa Salloum, Said A. |
| author_sort | Chaker, Mhamdi |
| collection | UMP |
| description | Nowadays, social media has swiftly altered the media landscape resulting in a competitive environment of news creation and dissemination. Sharing news through social media websites is almost provided in a textual format. The nature of the disseminated text is considered as unstructured text. Text mining techniques play a significant role in transforming the unstructured text into informative knowledge with various interesting patterns. Due to the lack of literature on textual analysis of news channels’ in social media, the current study seeks to explore this genre of new media discourse through analyzing news channels online textual data and transforming its quantifiable information into constructive knowledge. Accordingly, this study applies various text mining techniques on this under-researched context aiming at extracting knowledge from unstructured textual data. To this end, three news channels have been selected, namely Fox News, CNN, and ABC News. Data has been collected from the Facebook pages of these three news channels through Facepager tool which was then processed using RapidMiner tool. Findings indicated that USA elections news received the highest coverage among others in these channels. Moreover, results revealed that the most frequent shared posts regarding the USA elections were tackled by the CNN followed by ABC News, and Fox News, respectively. Additionally, results revealed a significant relationship between ABC News and CNN in covering similar topics. |
| first_indexed | 2024-03-06T12:24:59Z |
| format | Book Chapter |
| id | UMPir21628 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:24:59Z |
| publishDate | 2017 |
| publisher | Springer |
| record_format | dspace |
| spelling | UMPir216282019-03-20T04:22:37Z http://umpir.ump.edu.my/id/eprint/21628/ Text mining and analytics a case study from news channels posts on Facebook Chaker, Mhamdi Al-Emran, Mostafa Salloum, Said A. QA76 Computer software Nowadays, social media has swiftly altered the media landscape resulting in a competitive environment of news creation and dissemination. Sharing news through social media websites is almost provided in a textual format. The nature of the disseminated text is considered as unstructured text. Text mining techniques play a significant role in transforming the unstructured text into informative knowledge with various interesting patterns. Due to the lack of literature on textual analysis of news channels’ in social media, the current study seeks to explore this genre of new media discourse through analyzing news channels online textual data and transforming its quantifiable information into constructive knowledge. Accordingly, this study applies various text mining techniques on this under-researched context aiming at extracting knowledge from unstructured textual data. To this end, three news channels have been selected, namely Fox News, CNN, and ABC News. Data has been collected from the Facebook pages of these three news channels through Facepager tool which was then processed using RapidMiner tool. Findings indicated that USA elections news received the highest coverage among others in these channels. Moreover, results revealed that the most frequent shared posts regarding the USA elections were tackled by the CNN followed by ABC News, and Fox News, respectively. Additionally, results revealed a significant relationship between ABC News and CNN in covering similar topics. Springer 2017-11-18 Book Chapter PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/21628/1/5.%20Text%20Mining%20and%20Analytics%20A%20Case%20Study%20from%20News%20Channels%20Posts%20on%20Facebook.pdf Chaker, Mhamdi and Al-Emran, Mostafa and Salloum, Said A. (2017) Text mining and analytics a case study from news channels posts on Facebook. In: Intelligent Natural Language Processing: Trends and Applications. Springer, Berlin, Germany, pp. 399-415. ISBN 9783319670560 https://doi.org/10.1007/978-3-319-67056-0_19 https://doi.org/10.1007/978-3-319-67056-0_19 |
| spellingShingle | QA76 Computer software Chaker, Mhamdi Al-Emran, Mostafa Salloum, Said A. Text mining and analytics a case study from news channels posts on Facebook |
| title | Text mining and analytics a case study from news channels posts on Facebook |
| title_full | Text mining and analytics a case study from news channels posts on Facebook |
| title_fullStr | Text mining and analytics a case study from news channels posts on Facebook |
| title_full_unstemmed | Text mining and analytics a case study from news channels posts on Facebook |
| title_short | Text mining and analytics a case study from news channels posts on Facebook |
| title_sort | text mining and analytics a case study from news channels posts on facebook |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/21628/1/5.%20Text%20Mining%20and%20Analytics%20A%20Case%20Study%20from%20News%20Channels%20Posts%20on%20Facebook.pdf |
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