Lavanya, P. G. and Suresha, M. (2017) Automatic summarization and visualisation of healthcare tweets. In: 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 13-16 Sept. 2017, Udupi, India.
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With social media encompassing people in all aspects of life, the relevance of information shared over these media is becoming highly relevant. The marketing and retail industry have been using social media like Twitter and Facebook extensively to collect information and promote their products. Now, it is the healthcare industry's turn to find hidden insights from the vast data available on the web. Analysing healthcare related tweets is one such arena which is proving to be useful in finding a lot of information about healthcare facilities like symptoms, diagnosis, treatment and recovery related to specific chronic diseases. As the data generated is huge, a summarized representation of the same is an important and non-trivial requirement which needs to be explored. In this work, we concentrate on analysing tweets related to cancer. We propose a simple clustering based method to summarize the Twitter generated data and extract more relevant tweets. In addition to this, two feature selection methods have been explored and the results compared which reiterates the importance of proper feature selection techniques in the process of Data analysis. The automatically generated summaries are evaluated using Cosine similarity measure. We also visualize the most frequent words using a Word cloud visualisation technique. Our work gives positive results and emphasises the fact that summarization of tweets provides a better understanding of the underlying data which can benefit healthcare industry which is aiming to provide personalised medicine for individuals.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | cancer;data analysis;data visualisation;feature selection;health care;medical computing;pattern clustering;social networking (online);healthcare tweets;social media;Twitter;healthcare industry;healthcare facilities;specific chronic diseases;summarized representation;feature selection methods;Data analysis;automatically generated summaries;Word cloud visualisation technique;healthcare related tweets;automatic summarization;Facebook;cancer;clustering based method;Cosine similarity measure;Feature extraction;Twitter;Cancer;Industries;Data mining;Clustering;Centroid;Feature Selection;Laplacian Score;Summarization;Tweets;Twitter;Variance;Visualisation |
| Subjects: | D Physical Science > Computer Science |
| Divisions: | Department of > Computer Science |
| Depositing User: | C Swapna Library Assistant |
| Date Deposited: | 08 Jul 2019 10:24 |
| Last Modified: | 08 Jul 2019 10:24 |
| URI: | http://eprints.uni-mysore.ac.in/id/eprint/4904 |
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