Study on the method of identifying opinion leaders based on online customer reviews

Author

Yu-tao, Ma ; Shu-qin, Cai ; Rui, Wang

Author_Institution

Sch. of Manage., Huazhong Univ. of Sci. & Technol., Wuhan, China

fYear

2011

fDate

13-15 Sept. 2011

Firstpage

10

Lastpage

17

Abstract

The deepening adoption of Web2.0 technology causes more and more users to publish reviews on the web about products, services, brands or business, and the online customer reviews (OCR) greatly influence customers´ purchasing decisions and corporate reputations. Therefore, it has significant value for enterprises to identify the opinion leaders of OCR. This study proposes a RFMS model to measure the influential power of OCR publisher combining RFM model and automatically measuring method of sentiment words, then identify opinion leaders by applying artificial neural network, finally assess the validity of identifying results based on the degree of centrality. This research analysis the online reviews of dianping.com, and make a data verification of the proposed method. Results show that the proposed method in this paper can accurately identify opinion leaders.

Keywords

Internet; customer satisfaction; marketing data processing; neural nets; RFMS model; Web 2.0 technology; artificial neural network; centrality degree; corporate reputation; customer purchasing decision; online customer review; opinion leader identification method; recency-frequency-monetary value model; Artificial neural networks; Internet; Lead; Optical character recognition software; Tagging; Time frequency analysis; Training; RFM; identify method; online customer reviews; opinion leader; sentiment;

fLanguage

English

Publisher

ieee

Conference_Titel

Management Science and Engineering (ICMSE), 2011 International Conference on

Conference_Location

Rome

ISSN

2155-1847

Print_ISBN

978-1-4577-1885-4

Type

conf

DOI

10.1109/ICMSE.2011.6069936

Filename

6069936