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- W3092209896 abstract "In today’s world of digitization, information is increasing at an exponential rate due to the ubiquitous nature of social media and web sources. With the advancement in Social Signal Processing, Social Informatics & Computing, and big data mining techniques, we can use this information in the health domain to determine the trend in the spread of symptoms and risk factors of diseases temporally. In this paper, our primary focus is to study coverage and evolution of risk factors of 19 most common Cancers in the last ten years (2009–2018) from the pieces of evidence collected from Tweets (Social Signal) and Wikipedia (Web Data) and demonstrate the relevant findings. Moreover, temporal variations are also shown in coverage of each cancer and risk factors to determine their evolution over time. We try to find the answers of questions like, Do different information sources show different risk factors for the same cancer ? or Is there any visible and distinctive trend in the temporal variation of any specific cancer or its risk factors? Each of the analysis unfolds various exciting observations. The most important among these is that some risk factors have the most adverse effects according to the one information source, but they are not at all harmful according to the other. Finally, the correlation of information sources, i.e., social signals and web data, is shown concerning variation in coverage of cancers and risk factors." @default.
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- W3092209896 date "2020-01-01" @default.
- W3092209896 modified "2023-09-25" @default.
- W3092209896 title "Coverage and Evolution of Cancer and Its Risk Factors - A Quantitative Study with Social Signals and Web-Data" @default.
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- W3092209896 doi "https://doi.org/10.1007/978-3-030-60975-7_9" @default.
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