Journal of Information Systems Engineering and Management

A Review of Usage and Applications of Social Media Analytics
Shadrack Stephen Madila 1 * , Mussa Ally Dida 1, Shubi Kaijage 1
More Detail
1 School of Computational & Communication Science and Engineering (CoCSE) Nelson Mandela African Institution of Science and Technology (NM-AIST), TANZANIA
* Corresponding Author
Review Article

Journal of Information Systems Engineering and Management, 2021 - Volume 6 Issue 3, Article No: em0141
https://doi.org/10.21601/jisem/10958

Published Online: 28 May 2021

Views: 317 | Downloads: 211

How to cite this article
APA 6th edition
In-text citation: (Madila et al., 2021)
Reference: Madila, S. S., Dida, M. A., & Kaijage, S. (2021). A Review of Usage and Applications of Social Media Analytics. Journal of Information Systems Engineering and Management, 6(3), em0141. https://doi.org/10.21601/jisem/10958
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Madila SS, Dida MA, Kaijage S. A Review of Usage and Applications of Social Media Analytics. J INFORM SYSTEMS ENG. 2021;6(3):em0141. https://doi.org/10.21601/jisem/10958
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Madila SS, Dida MA, Kaijage S. A Review of Usage and Applications of Social Media Analytics. J INFORM SYSTEMS ENG. 2021;6(3), em0141. https://doi.org/10.21601/jisem/10958
Chicago
In-text citation: (Madila et al., 2021)
Reference: Madila, Shadrack Stephen, Mussa Ally Dida, and Shubi Kaijage. "A Review of Usage and Applications of Social Media Analytics". Journal of Information Systems Engineering and Management 2021 6 no. 3 (2021): em0141. https://doi.org/10.21601/jisem/10958
Harvard
In-text citation: (Madila et al., 2021)
Reference: Madila, S. S., Dida, M. A., and Kaijage, S. (2021). A Review of Usage and Applications of Social Media Analytics. Journal of Information Systems Engineering and Management, 6(3), em0141. https://doi.org/10.21601/jisem/10958
MLA
In-text citation: (Madila et al., 2021)
Reference: Madila, Shadrack Stephen et al. "A Review of Usage and Applications of Social Media Analytics". Journal of Information Systems Engineering and Management, vol. 6, no. 3, 2021, em0141. https://doi.org/10.21601/jisem/10958
ABSTRACT
This paper presents the report of a social media analytics (SMA) review. The review conducted to find out the methods and tools used in social media analytics, types of social media platforms which the SMA are performed and the field which SMA has been performed. Social media contains a lot of user uploaded data in different formats like text, images, photos, video etc. These large volumes of data are converted in meaningful information which can be understood using different methods and tools which are called social media analytics. A literature review of articles published between 2010-2020 has been conducted using articles obtained from reputable databases IEEE Xplore, ACM digital, Emerald insight, Springer Link and Science direct. A number of 44 articles have been selected for review from 110 retrieved papers. The paper has been reviewed according to the study objectives. The study found that SMA tools and techniques which have been used are sentiment analysis, youtube analytics, visible intelligence, IBM Watson tool and predictive models. The social media platforms which were mostly used are twitter, facebook, youtube, trip advisor and blogs. SMA has been observed in different fields like agriculture, politics, health, social and business sector.
KEYWORDS
REFERENCES
  • Al Kubaizi, R., Al-Otaibi, S., Al Washigry, B., Al Suhaim, E., Al Sughayer, J. and Al Jumaiah, R. (2018). Mining Expertise Using Social Media Analytics. 2018 1st International Conference on Computer Applications & Information Security (ICCAIS), Riyadh. https://doi.org/10.1109/CAIS.2018.8442014
  • Babu, A. G., Kumari, S. S. and Kamakshaiah, K. (2017). An Experimental Analysis of Clustering Sentiments for Opinion Mining. Proceedings of the 2017 International Conference on Machine Learning and Soft Computing - ICMLSC ‘17. https://doi.org/10.1145/3036290.3036318
  • Barrelet, C. J., Kuzulugil, S. S. and Bener, A. B. (2016). The Twitter Bullishness Index. Proceedings of the 20th International Database Engineering & Applications Symposium on - IDEAS ‘16. https://doi.org/10.1145/2938503.2938508
  • Beigi, G., Hu, X., Maciejewski, R. and Liu, H. (2016). An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief. Studies in Computational Intelligence, 313-340. https://doi.org/10.1007/978-3-319-30319-2_13
  • Bukhari, I., Wojtalewicz, C., Vorvoreanu M. and Dietz, J. E. (2012). Social media use for large event management: The application of social media analytic tools for the Super Bowl XLVI. 2012 IEEE Conference on Technologies for Homeland Security (HST), Waltham, MA, pp. 24-29. https://doi.org/10.1109/THS.2012.6459821
  • Buus Lassen, N., la Cour, L. and Vatrapu, R. (2017). Predictive Analytics with Social Media Data. In L. Sloan & A. Quan-Haase (Eds.), The SAGE Handbook of Social Media Research Methods (pp. 328-341). London: SAGE Publications. https://doi.org/10.4135/9781473983847.n20
  • Chang, Y.-C., Ku, C.-H. and Chen, C.-H. (2017). Social media analytics: Extracting and visualizing Hilton hotel ratings and reviews from TripAdvisor. International Journal of Information Management, 48, 263-279. https://doi.org/10.1016/j.ijinfomgt.2017.11.001
  • Chumwatana, T. and Wongkolkitsilp, T. (2019). Using Classification Technique for Customer Relationship Management based on Thai Social Media Data. In Proceedings of the 2019 11th International Conference on Computer and Automation Engineering (ICCAE 2019). Association for Computing Machinery, New York, NY, USA, pp. 7-11. https://doi.org/10.1145/3313991.3314010
  • Culotta, A. (2010). Towards detecting influenza epidemics by analyzing Twitter messages. Proceedings of the First Workshop on Social Media Analytics - SOMA ‘10. https://doi.org/10.1145/1964858.1964874
  • Cvijikj, I. P. and Michahelles, F. (2011). Understanding social media marketing. Proceedings of the 15th International Academic MindTrek Conference on Envisioning Future Media Environments - MindTrek ‘11. https://doi.org/10.1145/2181037.2181066
  • Dahal, B., Kumar, S. A. P. and Li, Z. (2019). Topic modeling and sentiment analysis of global climate change tweets. Social Network Analysis and Mining, 9, 24. https://doi.org/10.1007/s13278-019-0568-8
  • Das, M. and Das, G. (2015). Structured analytics in social media. Proceedings of the VLDB Endowment, 8(12), 2046-2047. https://doi.org/10.14778/2824032.2824135
  • del Rocío Bonilla Quijada, M., Arriaga, J. L. D. O. and Domingo, D. A. (2020). Insights into user engagement on social media. Findings from two fashion retailers. Electron Markets. https://doi.org/10.1007/s12525-020-00429-0
  • Dias, D. S., Welikala M. D. and Dias, N. G. J. (2018). Identifying Racist Social Media Comments in Sinhala Language Using Text Analytics Models with Machine Learning. 2018 18th International Conference on Advances in ICT for Emerging Regions (ICTer), Colombo, Sri Lanka. https://doi.org/10.1109/ICTER.2018.8615492
  • Domínguez-Navarro, S. and González-Rodríguez, M. (2020). Social Media managerial implications for budget accommodation venues: use of Social Media platforms more effectively and efficiently. Quality & Quantity, 54, 1671-1689. https://doi.org/10.1007/s11135-019-00932-3
  • Dong, H., Halem M. and Zhou, S. (2013).Social Media Data Analytics Applied to Hurricane Sandy. 2013 International Conference on Social Computing, Alexandria, VA. https://doi.org/10.1109/SocialCom.2013.152
  • Drus, D. and Khalid, H. (2019). Sentiment analysis in social media and its application: Systematic literature review. Procedia Computer Science, 161, 707-714, https://doi.org/10.1016/j.procs.2019.11.174
  • Ghosh, S., Srijith, P. K. and Desarkar, M. S. (2017). Using social media for classifying actionable insights in disaster scenario. International Journal of Advances in Engineering Sciences and Applied Mathematics, 9(4), 224-237. https://doi.org/10.1007/s12572-017-0197-2
  • Ghriga, M., Shang, R. and Shurriah, R. (2016). Discovering community development information from social media: a social media analytics project using IBM BlueMix: faculty poster abstract. Journal of Computing Sciences in Colleges, 31(6), 52-54.
  • He, W., Tian, X. and Wang, F.-K. (2019). Innovating the customer loyalty program with social media: A case study of best practices using analytics tools. Journal of Enterprise Information Management, 32(5), 807-823. https://doi.org/10.1108/JEIM-10-2018-0224
  • He, W., Tian, X., Tao, R., Zhang, W., Yan, G. and Akula, V. (2017). Application of social media analytics: a case of analyzing online hotel reviews. Online Information Review, 41(7), 921-935. https://doi.org/10.1108/OIR-07-2016-0201
  • Hong Y. and Sinnott R. O. (2018) A Social Media Platform for Infectious Disease Analytics. In: O. Gervasi et al. (Eds.), Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science (vol. 10960). Springer, Cham. https://doi.org/10.1007/978-3-319-95162-1_36
  • Indrawati and Alamsyah, A. (2017). Social network data analytics for market segmentation in Indonesian telecommunications industry. 2017 5th International Conference on Information and Communication Technology (ICoIC7), Malacca City, pp. 1-5. https://doi.org/10.1109/ICoICT.2017.8074677
  • Jain, A. K., Kumar, A., Garg, J., Patange, U. and Jalan, P. (2015). TraffTrend. Proceedings of the 2nd IKDD Conference on Data Sciences - CODS-IKDD ‘15. https://doi.org/10.1145/2778865.2778875
  • Jansen, B. J., Jung, S., Salminen, J., An J. and Kwa, H. (2017). Leveraging Social Analytics Data for Identifying Customer Segments for Online News Media. 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), Hammamet, pp. 463-468. https://doi.org/10.1109/AICCSA.2017.64
  • Kannan, R., Govindasamy, M. A., Soon, L. and Ramakrishnan, K. (2018). Social Media Analytics for Dengue Monitoring in Malaysia. 2018 8th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), Penang, Malaysia. https://doi.org/10.1109/ICCSCE.2018.8685028
  • Khaleq, A. A. and Ra, I. (2018). Twitter Analytics for Disaster Relevance and Disaster Phase Discovery. Advances in Intelligent Systems and Computing, pp. 401-417. https://doi.org/10.1007/978-3-030-02686-8_31
  • Kursuncu, U., Gaur, M., Lokala, U., Thirunarayan, K., Sheth, A. and Arpinar, I. B. (2018). Predictive Analysis on Twitter: Techniques and Applications. Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining, pp. 67-104. https://doi.org/10.1007/978-3-319-94105-9_4
  • Martinez, L. S., Tsou, M.-H. and Spitzberg, B. H. (2019). A case study in belief surveillance, sentiment analysis, and identification of informational targets for e-cigarettes interventions. Proceedings of the 10th International Conference on Social Media and Society - SMSociety ‘19. https://doi.org/10.1145/3328529.3328540
  • Palmatier, R. W., Houston, M. B. and Hulland, J. (2018). Review articles: purpose, process, and structure. Journal of the Academy of Marketing Science, 46, 1-5. https://doi.org/10.1007/s11747-017-0563-4
  • Park, S. B., Jang, J. and Ok, C. M. (2016). Analyzing Twitter to explore perceptions of Asian restaurants. Journal of Hospitality and Tourism Technology, 7(4), 405-422. https://doi.org/10.1108/JHTT-08-2016-0042
  • Peña-Araya, V., Quezada, M., Poblete, B. and Parra, D. (2017). Gaining historical and international relations insights from social media: spatio-temporal real-world news analysis using Twitter. EPJ Data Science, 6(1), 25. https://doi.org/10.1140/epjds/s13688-017-0122-8
  • Rahmani, A., Chen, A., Sarhan, A., Jida, J., Rifaie, M. and Alhajj, R. (2014). Social media analysis and summarization for opinion mining: a business case study. Social Network Analysis and Mining, 4(1), 171. https://doi.org/10.1007/s13278-014-0171-y
  • Sachdeva, S. and McCaffrey, S. (2018). Using Social Media to Predict Air Pollution during California Wildfires. Proceedings of the 9th International Conference on Social Media and Society - SMSociety ‘18. https://doi.org/10.1145/3217804.3217946
  • Santander, P., Alfaro, R., Allende-Cid, H., Elortegui, C. and González Arias, C. (2020). Analyzing social media, analyzing the social? A methodological discussion about the demoscopic and predictive potential of social media. Quality & Quantity, 54, 903-923. https://doi.org/10.1007/s11135-020-00965-z
  • Saravanan, M. and Perepu, S. K. (2019). Realizing Social-Media-Based Analytics for Smart Agriculture. Review of Socionetwork Strategies, 13, 33-53. https://doi.org/10.1007/s12626-019-00035-3
  • Sijtsma, B., Qvarfordt, P. and Chen, F. (2016). Tweetviz. Visualizing tweets for business intelligence. Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR ‘16. https://doi.org/10.1145/2911451.2911470
  • Singh, A., Shukla, N. and Mishra, N. (2018). Social media data analytics to improve supply chain management in food industries. Transportation Research Part E: Logistics and Transportation Review, 114, 398-415. https://doi.org/10.1016/j.tre.2017.05.008
  • Stieglitz, S. and Dang-Xuan, L. (2012). Social media and political communication: a social media analytics framework. Social Network Analysis and Mining, 3(4), 1277-1291. https://doi.org/10.1007/s13278-012-0079-3
  • Stieglitz, S., Dang-Xuan, L., Bruns, A. and Neuberger, C. (2014). Social Media Analytics. Business & Information Systems Engineering, 6(2), 89-96. https://doi.org/10.1007/s12599-014-0315-7
  • Su, C. and Chen, Y. (2016). Social Media Analytics Based Product Improvement Framework. 2016 International Symposium on Computer, Consumer and Control (IS3C), Xi’an, pp. 393-396. https://doi.org/10.1109/IS3C.2016.107
  • Tian, X., He, W., Tang, C., Li, L., Xu, H. and Selover, D. (2019). A new approach of social media analytics to predict service quality: evidence from the airline industry. Journal of Enterprise Information Management, 33(1), 51-70. https://doi.org/10.1108/JEIM-03-2019-0086
  • Udanor, C. and Anyanwu, C. C. (2019). Combating the challenges of social media hate speech in a polarized society: A Twitter ego lexalytics approach. Data Technologies and Applications, 53(4), 501-527. https://doi.org/10.1108/DTA-01-2019-0007
  • Udanor, C., Aneke, S. and Ogbuokiri, B.O. (2016). Determining social media impact on the politics of developing countries using social network analytics. Program: electronic library and information systems, 50(4), 481-507. https://doi.org/10.1108/PROG-02-2016-0011
  • Von Hoffen, M., Hagge, M., Betzing, J. H. and Chasin, F. (2017). Leveraging social media to gain insights into service delivery: a study on Airbnb. Information Systems and e-Business Management, 16(2), 247-269. https://doi.org/10.1007/s10257-017-0358-7
  • Vorvoreanu, M., Boisvenue, G. A., Wojtalewicz, C. J. and Dietz, E. J. (2013). Social media marketing analytics: A case study of the public’s perception of Indianapolis as Super Bowl XLVI host city. Journal of Direct, Data and Digital Marketing Practice, 14(4), 321-328. https://doi.org/10.1057/dddmp.2013.18
  • Weiler, A., Scholl, M. H., Wanner, F. and Rohrdantz, C. (2013). Event identification for local areas using social media streaming data. Proceedings of the ACM SIGMOD Workshop on Databases and Social Networks - DBSocial ‘13. https://doi.org/10.1145/2484702.2484703
  • Wu He, Xin Tian, Ran Tao, Weidong Zhang, Gongjun Yan, Vasudeva Akula, (2017). Application of social media analytics: a case of analyzing online hotel reviews. Online Information Review, 41(7), 921-935. https://doi.org/10.1108/OIR-07-2016-0201
  • Wu, G. J., Xu, Z., Tajdini, S., Zhang, J. and Song, L. (2019). Unlocking value through an extended social media analytics framework: Insights for new product adoption. Qualitative Market Research, 22(2), 161-179. https://doi.org/10.1108/QMR-01-2017-0044
  • Xiang, Z., Du, Q., Ma, Y. and Fan, W. (2017). A comparative analysis of major online review platforms: implications for social media analytics in hospitality and tourism. Tourism Management, 58, 51-65. https://doi.org/10.1016/j.tourman.2016.10.001
  • Xiang, Z., Schwartz, Z. and Uysal, M. (2016). Market Intelligence: Social Media Analytics and Hotel Online Reviews. Tourism on the Verge, 281-295. https://doi.org/10.1007/978-3-319-44263-1_16
  • Xu, Z., Lachlan, K., Ellis, L. and Rainear, A. M. (2019). Understanding public opinion in different disaster stages: a case study of Hurricane Irma. Internet Research. 30(2), 695-709. https://doi.org/10.1108/INTR-12-2018-0517
  • Yuheng Hu, Ajita John, and Doree Duncan Seligmann. 2011. Event analytics via social media. In Proceedings of the 2011 ACM workshop on Social and behavioural networked media access (SBNMA ‘11). Association for Computing Machinery, New York, NY, USA, 39-44. https://doi.org/10.1145/2072627.2072638
  • Zeng, D., Chen, H., Lusch, R. and Li, S.-H. (2010). Social Media Analytics and Intelligence. Intelligent Systems, 26(6), 13-16. https://doi.org/10.1109/MIS.2010.151
LICENSE
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.