Review on the Role of Social Media for Dengue Prevention and Monitoring

Article Preview

Abstract:

With the emerging of social media as a platform of interaction, users are now connected with all around the world. This connection enhances dissemination of information from users. Examples of social platforms which are highly used among users are Facebook and Twitter. Recently WHO stated that dengue is currently rising among the countries in the World. In Malaysia, the number of dengue cases are currently rising at an alarming stage where it exceeds the number of last year’s dengue cases. Although traditional methods of distributing surveys and conducting awareness about dengue has been done, positive responses from those efforts are little. In this paper, we have surveyed the feasibility of engaging social media like Twitter for monitoring and preventing dengue. Tweets related to dengue will be analyzed using emotion detection techniques, aiming to identify tweets that generate positive emotion, which in return helpful for dengue monitoring and prevention. Since most of tweets are written in Malay language by Malaysians, a proper dictionary is needed to analyze the emotion of users. The outcome from this study will be beneficial for dengue prevention and monitoring by detecting how Malaysians are actually tweeting and reacting to dengue cases in Malaysia.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

228-233

Citation:

Online since:

June 2019

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2019 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Sosnowy, C., & Collette. (2014). Practicing Patienthood Online: Social Media, Chronic Illness, and Lay Expertise. Societies, 4(2), 316–329.

DOI: 10.3390/soc4020316

Google Scholar

[2] Antheunis, M. L., Tates, K., & Nieboer, T. E. (2013). Patients' and health professionals' use of social media in health care: Motives, barriers and expectations. Patient Education and Counseling, 92(3), 426–431. 10.

DOI: 10.1016/j.pec.2013.06.020

Google Scholar

[3] Wong, L. P., Shakir, S. M. M., Atefi, N., AbuBakar, S., Isa, A., Loke, Y., … Staines, A. (2015). Factors Affecting Dengue Prevention Practices: Nationwide Survey of the Malaysian Public. PLOS ONE, 10(4), e0122890.

DOI: 10.1371/journal.pone.0122890

Google Scholar

[4] Vinay Kumar Jain, S. K. (2017). Effective Surveillance and Predictive Mapping of Mosquito-Borne diseases using social media. Effective Surveillance and Predictive Mapping of Mosquito-Borne Diseases Using Social Media.

DOI: 10.1016/j.jocs.2017.07.003

Google Scholar

[5] Batrinca, B., & Treleaven, P. C. (2015). Social media analytics: a survey of techniques, tools and platforms. AI & SOCIETY, 30(1), 89–116.

DOI: 10.1007/s00146-014-0549-4

Google Scholar

[6] Lwin, M. O., Vijaykumar, S., Noel, O., Fernando, N., Cheong, S. A., Sampath Rathnayake, V., Foo, S. (2014). A 21st century approach to tackling dengue: Crowdsourced surveillance, predictive mapping and tailored communication. Acta Tropica, 130, 100–107.

DOI: 10.1016/j.actatropica.2013.09.021

Google Scholar

[7] Sayavong, C., Chompikul, J., Wongsawass, S., & Rattanapan, C. (2015). Knowledge, attitudes and preventive behaviors related to dengue vector breeding control measures among adults in communities of Vientiane, capital of the Lao PDR. Journal of Infection and Public Health, 8, 466–473.

DOI: 10.1016/j.jiph.2015.03.005

Google Scholar

[8] Smailhodzic, E., Hooijsma, W., Boonstra, A., & Langley, D. J. (2016). Social media use in healthcare: A systematic review of effects on patients and on their relationship with healthcare professionals. BMC Health Services Research, 16(1), 442.

DOI: 10.1186/s12913-016-1691-0

Google Scholar

[9] Beaunoyer, E., Arsenault, M., Lomanowska, A. M., & Guitton, M. J. (2017). Understanding online health information: Evaluation, tools, and strategies. Patient Education and Counseling, 100(2), 183–189.

DOI: 10.1016/j.pec.2016.08.028

Google Scholar

[10] Robert Herriman. (2017). Malaysia reports 8,000 dengue cases in January - Outbreak News Today.

Google Scholar

[11] WHO. (2017). Update on the Dengue Situation in the Western Pacific Region.

Google Scholar

[12] Budget 2017: RM25b allocated for healthcare boost | Malaysia | Malay Mail Online. (2017.).

Google Scholar

[13] Medhat, W., Hassan, A., & Korashy, H. (2014). Sentiment analysis algorithms and applications: A survey. Ain Shams Engineering Journal, 5(4), 1093–1113.

DOI: 10.1016/j.asej.2014.04.011

Google Scholar

[14] Chandra Pandey, A., Singh Rajpoot, D., & Saraswat, M. (2017). Twitter sentiment analysis using hybrid cuckoo search method. Information Processing and Management, 53, 764– 779.

DOI: 10.1016/j.ipm.2017.02.004

Google Scholar

[15] Alayba, A. M., Palade, V., England, M., & Iqbal, R. (2017). Arabic Language Sentiment Analysis on Health Services.

DOI: 10.1109/asar.2017.8067771

Google Scholar

[16] Perikos, I., & Hatzilygeroudis, I. (2016). Recognizing emotions in text using ensemble of classifiers.

DOI: 10.1016/j.engappai.2016.01.012

Google Scholar

[17] Kim, S., Bak, J., & Oh, A. (n.d.). Do You Feel What I Feel? Social Aspects of Emotions in Twitter Conversations.

DOI: 10.1609/icwsm.v6i1.14310

Google Scholar

[18] Andrea Ceron,Luigi Curini, S. M. L. (n.d.). iSA:A fast,scalable and accurate algorithm for sentiment analysis of social media content. (2016).

DOI: 10.1016/j.ins.2016.05.052

Google Scholar

[19] Saif, H., He, Y., Fernandez, M., & Alani, H. (2015). Contextual semantics for sentiment analysis of Twitter. Information Processing and Management, 52, 5–19. 05.

DOI: 10.1016/j.ipm.2015.01.005

Google Scholar

[20] Collomb, A., Costea, C., Joyeux, D., Hasan, O., & Brunie, L. (2013). A Study and Comparison of Sentiment Analysis Methods for Reputation Evaluation.

Google Scholar

[21] Boonchutima, S., Kachentawa, K., Limpavithayakul, M., & Prachansri, A. (2017). Longitudinal study of Thai people media exposure, knowledge, and behavior on dengue fever prevention and control. Journal of Infection and Public Health.

DOI: 10.1016/j.jiph.2017.01.016

Google Scholar