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Archetype-Based Modeling and Search of Social Media

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Department of Computer Science, Western University, London, ON N6A 5B7, Canada
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Faculty of Information & Media Studies, Western University, London, ON N6A 5B9, Canada
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Department of Biostatistics & Epidemiology, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5C1, Canada
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Author to whom correspondence should be addressed.
Big Data Cogn. Comput. 2019, 3(3), 44; https://doi.org/10.3390/bdcc3030044
Received: 29 June 2019 / Revised: 19 July 2019 / Accepted: 22 July 2019 / Published: 24 July 2019
Existing keyword-based search techniques suffer from limitations owing to unknown, mismatched, and obscure vocabulary. These challenges are particularly prevalent in social media, where slang, jargon, and memetics are abundant. We develop a new technique, Archetype-Based Modeling and Search, that can mitigate these challenges as they are encountered in social media. This technique learns to identify new relevant documents based on a specified set of archetypes from which both vocabulary and relevance information are extracted. We present a case study from the social media data from Reddit, by using authors from /r/Opiates to characterize discourse around opioid use and to find additional relevant authors on this topic. View Full-Text
Keywords: information retrieval; modeling; social media; big data; machine learning; deep learning; natural language processing; word embeddings; opioids information retrieval; modeling; social media; big data; machine learning; deep learning; natural language processing; word embeddings; opioids
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Davis, B.D.; Sedig, K.; Lizotte, D.J. Archetype-Based Modeling and Search of Social Media. Big Data Cogn. Comput. 2019, 3, 44.

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