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Sentiment lexicons for health-related opinion mining

หน่วยงาน Nanyang Technological University, Singapore

รายละเอียด

ชื่อเรื่อง : Sentiment lexicons for health-related opinion mining
นักวิจัย : Goeuriot, Lorraine , Na, Jin-Cheon , Min Kyaing, Wai Yan , Khoo, Christopher S. G. , Chang, Yun-Ke , Theng, Yin-Leng , Kim, Jung-jae
คำค้น : DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences.
หน่วยงาน : Nanyang Technological University, Singapore
ผู้ร่วมงาน : -
ปีพิมพ์ : 2555
อ้างอิง : Goeuriot, L., Na, J.-C., Min Kyaing, W. Y., Khoo, C. S. G., Chang, Y.-K., Theng, Y.-L., et al. (2012). Sentiment lexicons for health-related opinion mining. Proceedings of the 2nd ACM SIGHIT symposium on International health informatics-IHI '12, pp219-226. , http://hdl.handle.net/10220/16673 , http://dx.doi.org/10.1145/2110363.2110390
ที่มา : -
ความเชี่ยวชาญ : -
ความสัมพันธ์ : -
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

Opinion mining consists in extracting from a text opinions expressed by its author and their polarity. Lexical resources, such as polarized lexicons, are needed for this task. Opinion mining in the medical domain has not been well explored, partly because little credence is given to patients and their opinions (although more and more of them are using social media). We are interested in opinion mining of user-generated content on drugs/medication. We present in this paper the creation of our lexical resources and their adaptation to the medical domain. We first describe the creation of a general lexicon, containing opinion words from the general domain and their polarity. Then we present the creation of a medical opinion lexicon, based on a corpus of drug reviews. We show that some words have a different polarity in the general domain and in the medical one. Some words considered generally as neutral are opinionated in medical texts. We finally evaluate the lexicons and show with a simple algorithm that using our general lexicon gives better results than other well-known ones on our corpus and that adding the domain lexicon improves them as well.

บรรณานุกรม :
Goeuriot, Lorraine , Na, Jin-Cheon , Min Kyaing, Wai Yan , Khoo, Christopher S. G. , Chang, Yun-Ke , Theng, Yin-Leng , Kim, Jung-jae . (2555). Sentiment lexicons for health-related opinion mining.
    กรุงเทพมหานคร : Nanyang Technological University, Singapore.
Goeuriot, Lorraine , Na, Jin-Cheon , Min Kyaing, Wai Yan , Khoo, Christopher S. G. , Chang, Yun-Ke , Theng, Yin-Leng , Kim, Jung-jae . 2555. "Sentiment lexicons for health-related opinion mining".
    กรุงเทพมหานคร : Nanyang Technological University, Singapore.
Goeuriot, Lorraine , Na, Jin-Cheon , Min Kyaing, Wai Yan , Khoo, Christopher S. G. , Chang, Yun-Ke , Theng, Yin-Leng , Kim, Jung-jae . "Sentiment lexicons for health-related opinion mining."
    กรุงเทพมหานคร : Nanyang Technological University, Singapore, 2555. Print.
Goeuriot, Lorraine , Na, Jin-Cheon , Min Kyaing, Wai Yan , Khoo, Christopher S. G. , Chang, Yun-Ke , Theng, Yin-Leng , Kim, Jung-jae . Sentiment lexicons for health-related opinion mining. กรุงเทพมหานคร : Nanyang Technological University, Singapore; 2555.