Salud María Jiménez-Zafra1, M Teresa Martín-Valdivia2, M Dolores Molina-González2, L Alfonso Ureña-López2. 1. Department of Computer Science, Advanced Studies Center in Information and Communication Technologies (CEATIC), Universidad de Jaén Campus Las Lagunillas, E-23071 Jaén, Spain. Electronic address: sjzafra@ujaen.es. 2. Department of Computer Science, Advanced Studies Center in Information and Communication Technologies (CEATIC), Universidad de Jaén Campus Las Lagunillas, E-23071 Jaén, Spain.
Abstract
OBJECTIVE: The main goal of this study is to examine how people express their opinion in medical forums. We analyze the language used in order to determine the best way to tackle sentiment analysis in this domain. METHODS: We have applied supervised learning and lexicon-based sentiment analysis approaches over two different corpora extracted from social web. Specifically, we have focused on two aspects: drugs and doctors. We have selected two forums and we have collected corpora for each one: (i) DOS, a Spanish corpus of drug reviews and (ii) COPOS, a Spanish corpus of patients' opinions about physicians. RESULTS: The classification results show that drug reviews are more difficult to classify than those about physicians. In order to understand the difference in the results, we have studied the linguistic features of both corpora. CONCLUSIONS: Although opinions about physicians and drugs are written in most cases by non-professional users, reviews about physicians are characterized by the use of an informal language while reviews about drugs are characterized by a combination of informal language with specific terminology (e.g. adverse effects, drug names) with greater lexical diversity, making the task of sentiment analysis difficult.
OBJECTIVE: The main goal of this study is to examine how people express their opinion in medical forums. We analyze the language used in order to determine the best way to tackle sentiment analysis in this domain. METHODS: We have applied supervised learning and lexicon-based sentiment analysis approaches over two different corpora extracted from social web. Specifically, we have focused on two aspects: drugs and doctors. We have selected two forums and we have collected corpora for each one: (i) DOS, a Spanish corpus of drug reviews and (ii) COPOS, a Spanish corpus of patients' opinions about physicians. RESULTS: The classification results show that drug reviews are more difficult to classify than those about physicians. In order to understand the difference in the results, we have studied the linguistic features of both corpora. CONCLUSIONS: Although opinions about physicians and drugs are written in most cases by non-professional users, reviews about physicians are characterized by the use of an informal language while reviews about drugs are characterized by a combination of informal language with specific terminology (e.g. adverse effects, drug names) with greater lexical diversity, making the task of sentiment analysis difficult.
Authors: Gabrielle Gurdin; Jorge A Vargas; Luke G Maffey; Amy L Olex; Nastassja A Lewinski; Bridget T McInnes Journal: AMIA Jt Summits Transl Sci Proc Date: 2020-05-30