TY - JOUR
T1 - A review for comparative text mining
T2 - From data acquisition to practical application
AU - Wei, Na
AU - Zhao, Songzheng
AU - Liu, Jing
AU - Wang, Shenghui
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China (grant number 71971170); and the Social Science Foundation of Shaanxi Province, China (grant number 2019P004); and the China Scholarship Council (grant number 202106290094).
Publisher Copyright:
© The Author(s) 2023.
PY - 2023/4/26
Y1 - 2023/4/26
N2 - Social media provides customers with great opportunities to share their opinions regarding certain products and services. Comparative text, as an important expression form, deserves further exploration, since it contains considerable comparative information between different products and services. In this study, we review existing research on Comparative Text Mining (CTM) in the past 16 years. Basic concepts related to CTM are first described, and a general research framework is subsequently proposed. We then dive into each component of the research framework, ranging from data acquisition, comparative text identification (CTI), comparative relation extraction (CRE), to potential applications. In addition, we conduct extensive experimental analysis on existing methods for CTI and CRE, and clarify their limitations. Accordingly, we provide corresponding insights, and point out future research directions.
AB - Social media provides customers with great opportunities to share their opinions regarding certain products and services. Comparative text, as an important expression form, deserves further exploration, since it contains considerable comparative information between different products and services. In this study, we review existing research on Comparative Text Mining (CTM) in the past 16 years. Basic concepts related to CTM are first described, and a general research framework is subsequently proposed. We then dive into each component of the research framework, ranging from data acquisition, comparative text identification (CTI), comparative relation extraction (CRE), to potential applications. In addition, we conduct extensive experimental analysis on existing methods for CTI and CRE, and clarify their limitations. Accordingly, we provide corresponding insights, and point out future research directions.
KW - 2023 OA procedure
U2 - 10.1177/01655515231165228
DO - 10.1177/01655515231165228
M3 - Article
SN - 0165-5515
SP - 1
EP - 13
JO - Journal of information science
JF - Journal of information science
ER -