Survey on Data Analysis in Social Media: A Practical Application Aspect
Social media has more than three billion users sharing events, comments, and feelings throughout the world. It serves as a critical information source with large volumes, high velocity, and a wide variety of data. The previous studies on information spreading, relationship analyzing, and individual...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2020-12-01
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| Series: | Big Data Mining and Analytics |
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| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2020.9020006 |
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| author | Qixuan Hou Meng Han Zhipeng Cai |
| author_facet | Qixuan Hou Meng Han Zhipeng Cai |
| author_sort | Qixuan Hou |
| collection | DOAJ |
| description | Social media has more than three billion users sharing events, comments, and feelings throughout the world. It serves as a critical information source with large volumes, high velocity, and a wide variety of data. The previous studies on information spreading, relationship analyzing, and individual modeling, etc., have been heavily conducted to explore the tremendous social and commercial values of social media data. This survey studies the previous literature and the existing applications from a practical perspective. We outline a commonly used pipeline in building social media-based applications and focus on discussing available analysis techniques, such as topic analysis, time series analysis, sentiment analysis, and network analysis. After that, we present the impacts of such applications in three different areas, including disaster management, healthcare, and business. Finally, we list existing challenges and suggest promising future research directions in terms of data privacy, 5G wireless network, and multilingual support. |
| format | Article |
| id | doaj-art-49f99bc97aba42d7a27d4aa9bf7fb075 |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2020-12-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-49f99bc97aba42d7a27d4aa9bf7fb0752025-02-02T03:45:09ZengTsinghua University PressBig Data Mining and Analytics2096-06542020-12-013425927910.26599/BDMA.2020.9020006Survey on Data Analysis in Social Media: A Practical Application AspectQixuan Hou0Meng Han1Zhipeng Cai2<institution>College of Computing, Georgia Institute of Technology</institution>, <city>Atlanta</city>, <state>GA</state> <postal-code>30332</postal-code>, <country>USA</country><institution>Data-driven Intelligence Research (DIR) Lab of College of Computing and Software Engineering, Kennesaw State University</institution>, <city>Kennesaw</city>, <state>GA</state> <postal-code>30060</postal-code>, <country>USA</country><institution content-type="dept">Department of Computer Science</institution>, <institution>Georgia State University</institution>, <city>Atlanta</city>, <state>GA</state> <postal-code>30303</postal-code>, <country>USA</country>Social media has more than three billion users sharing events, comments, and feelings throughout the world. It serves as a critical information source with large volumes, high velocity, and a wide variety of data. The previous studies on information spreading, relationship analyzing, and individual modeling, etc., have been heavily conducted to explore the tremendous social and commercial values of social media data. This survey studies the previous literature and the existing applications from a practical perspective. We outline a commonly used pipeline in building social media-based applications and focus on discussing available analysis techniques, such as topic analysis, time series analysis, sentiment analysis, and network analysis. After that, we present the impacts of such applications in three different areas, including disaster management, healthcare, and business. Finally, we list existing challenges and suggest promising future research directions in terms of data privacy, 5G wireless network, and multilingual support.https://www.sciopen.com/article/10.26599/BDMA.2020.9020006social mediatopic analysistime series analysissentiment analysisnetwork analysisdisaster managementbio-surveillancebusiness intelligence |
| spellingShingle | Qixuan Hou Meng Han Zhipeng Cai Survey on Data Analysis in Social Media: A Practical Application Aspect Big Data Mining and Analytics social media topic analysis time series analysis sentiment analysis network analysis disaster management bio-surveillance business intelligence |
| title | Survey on Data Analysis in Social Media: A Practical Application Aspect |
| title_full | Survey on Data Analysis in Social Media: A Practical Application Aspect |
| title_fullStr | Survey on Data Analysis in Social Media: A Practical Application Aspect |
| title_full_unstemmed | Survey on Data Analysis in Social Media: A Practical Application Aspect |
| title_short | Survey on Data Analysis in Social Media: A Practical Application Aspect |
| title_sort | survey on data analysis in social media a practical application aspect |
| topic | social media topic analysis time series analysis sentiment analysis network analysis disaster management bio-surveillance business intelligence |
| url | https://www.sciopen.com/article/10.26599/BDMA.2020.9020006 |
| work_keys_str_mv | AT qixuanhou surveyondataanalysisinsocialmediaapracticalapplicationaspect AT menghan surveyondataanalysisinsocialmediaapracticalapplicationaspect AT zhipengcai surveyondataanalysisinsocialmediaapracticalapplicationaspect |