Abstract
Regulators, analysts, policy-makers, and advocacy groups are increasingly interested in utilizing the abundance of available online Health 2.0 content to support key decision-making tasks. However, existing systems are ill-suited to deal with the plethora of medical spam and variety of relevant online channels. We present a prototype system for collecting, analyzing, aggregating, and presenting key topics and sentiments encompassed in online medical content. By incorporating modules for examining credibility, relevance, and context, the system is able to present users with information that is markedly better with respect to credibility, coverage, precision, and timeliness.
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References
Eysenbach, G.: Medicine 2.0: social networking, collaboration, participation, apomediation, and openness. J. Med. Internet Res. 10(3), e22 (2008)
Adjeroh, D., Beal, R., Abbasi, A., Zheng, W., Abate, M., Ross, A.: Signal fusion for social media analysis of adverse drug events. IEEE Intell. Syst. 29(2), 74–80 (2014)
Abbasi, A., Adjeroh, D.: Social media analytics for smart health. IEEE Intell. Syst. 29(2), 60–64 (2014)
Abbasi, A., Zahedi, F.M., Kaza, S.: Detecting fake medical web sites using recursive trust labeling. ACM Trans. Inf. Syst. 30(4), 22 (2012)
Fu, T., Abbasi, A., Zeng, D., Chen, H.: Sentimental spidering: leveraging opinion information in focused crawlers. ACM Trans. Inf. Syst. 30(4), 24 (2012)
Abbasi, A., Fu, T., Zeng D., Adjeroh, D.: Crawling credible online medical sentiments for social intelligence. In: The ASE/IEEE International Conference on Social Computing, Washington D.C., 8–14 September 2013
Fu, T., Abbasi, A., Chen, H.: A focused crawler for dark web forums. J. Am. Soc. Inform. Sci. Technol. 61(6), 1213–1231 (2010)
Tremayne, M., Zheng, N., Lee, J., Jeong, J.: Issue publics on the web: applying network theory to the war blogosphere. J. Comput.-Med. Commun. 12(1), 290–310 (2006)
Fu, T., Abbasi, A., Chen, H.: A hybrid approach to web forum interactional coherence analysis. J. Am. Soc. Inform. Sci. Technol. 59(8), 1195–1209 (2008)
Jensen, M.L., Lowry, P.B., Burgoon, J.K., Nunamaker, J.F.: Technology dominance in complex decision making: the case of aided credibility assessment. J. Manag. Inf. Syst. 27(1), 175–202 (2010)
Jensen, M.L., Averbeck, J.M., Zhang, Z., Wright, K.B.: Credibility of anonymous online product reviews: a language expectancy perspective. J. Manag. Inf. Syst. 30(1), 293–323 (2013)
Abbasi, A., Sarker, S., Chiang, R.H.L.: Big data research in information systems: toward an inclusive research agenda. J. Assoc. Inf. Syst. 17(2), 3 (2016)
Acknowledgements
We would like to thank the U.S. National Science Foundation for their support through grants IIS-1236970, IIS-1236983, IIS-1552860, and IIS-1553109.
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© 2016 Springer International Publishing Switzerland
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Abbasi, A., Zhao, K., Abraham, B. (2016). A Prototype System for Collecting and Analyzing Credible Online Medical Content. In: Parsons, J., Tuunanen, T., Venable, J., Donnellan, B., Helfert, M., Kenneally, J. (eds) Tackling Society's Grand Challenges with Design Science. DESRIST 2016. Lecture Notes in Computer Science(), vol 9661. Springer, Cham. https://doi.org/10.1007/978-3-319-39294-3_14
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DOI: https://doi.org/10.1007/978-3-319-39294-3_14
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