A consensus group decision making method for hotel selection with online reviews by sentiment analysis

被引：25

作者：

Wu, Jian ^{[1
,2
]}

Ma, Xiaoao ^{[1
,2
]}

Chiclana, Francisco ^{[3
,4
]}

Liu, Yujia ^{[1
,2
]}

Wu, Yang ^{[1
,2
]}

机构：

[1] Shanghai Maritime Univ, Sch Econ & Management, Shanghai 201306, Peoples R China

[2] Shanghai Maritime Univ, Ctr Artificial Intelligence & Decis Sci, Shanghai 201306, Peoples R China

[3] De Montfort Univ, Fac Comp Engn & Media, Inst Artificial Intelligence, Leicester, Leics, England

[4] Univ Granada, Andalusian Res Inst Data Sci & Computat Intellige, Granada, Spain

来源：

APPLIED INTELLIGENCE | 2022年 / 52卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Hotel selection; Online reviews; Sentiment analysis; Group consensus; Feedback mechanism; MINIMUM ADJUSTMENT; FEEDBACK MECHANISM; SOCIAL NETWORK; MODEL; CLASSIFICATION; PERFORMANCE; EXPERIENCE; RATINGS; HARMONY; COST;

D O I：

10.1007/s10489-021-02991-2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a framework for hotel selection based on online reviews by sentiment analysis from the perspective of consensus group decision making. To identify multi-granularity sentiment strength in text reviews, a sentiment analysis method based on the Word2Vec algorithm and one-vs-one strategy based Support Vector Machine (OVO-SVM) algorithm is provided. Then, richer information content can be derived from online text reviews, which are used as the data source of this study. To help members make an aggregation on the preference of hotel attributes, a consensus model with an improved feedback mechanism is proposed, which can reasonably control the adjustment cost in the consensus reaching process. Combining the hotel performance obtained from online reviews and the group preference consensus, the optimal hotel for members can be selected. At the end of this paper, a case study is presented to illustrate the use of the proposed method.

引用

页码：10716 / 10740

页数：25

共 62 条

[1]

[Anonymous], 2021, GROUP DECIS NEGOT, DOI DOI 10.1007/S10726--021--09756--9

[2]

[Anonymous], 2018, APPL INTELL, DOI DOI 10.1007/978-981-10-3229-5_86

[3]

[Anonymous], 2021, INFORM FUSION, DOI DOI 10.1016/J.INFFUS.2020.10.010

[4] Successes and challenges in developing a hybrid approach to sentiment analysis [J].

Appel, Orestes ;

Chiclana, Francisco ;

Carter, Jenny ;

Fujita, Hamido .

APPLIED INTELLIGENCE, 2018, 48 (05) :1176-1188

[5] A Consensus Approach to the Sentiment Analysis Problem Driven by Support-Based IOWA Majority [J].

Appel, Orestes ;

Chiclana, Francisco ;

Carter, Jenny ;

Fujita, Hamido .

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2017, 32 (09) :947-965

[6] Cross-ratio uninorms as an effective aggregation mechanism in sentiment analysis [J].

Appel, Orestes ;

Chiclana, Francisco ;

Carter, Jenny ;

Fujita, Hamido .

KNOWLEDGE-BASED SYSTEMS, 2017, 124 :16-22

[7] A hybrid approach to the sentiment analysis problem at the sentence level [J].

Appel, Orestes ;

Chiclana, Francisco ;

Carter, Jenny ;

Fujita, Hamido .

KNOWLEDGE-BASED SYSTEMS, 2016, 108 :110-124

[8]

Baber R., 2015, Pranjana: The Journal of Management Awareness, V18, P52, DOI [https://doi.org/10.5958/0974-0945.2015.00012.6, DOI 10.5958/0974-0945.2015.00012.6]

[9] Wisdom of crowds: Conducting importance-performance analysis (IPA) through online reviews [J].

Bi, Jian-Wu ;

Liu, Yang ;

Fan, Zhi-Ping ;

Zhang, Jin .

TOURISM MANAGEMENT, 2019, 70 :460-478

[10] An Extension of Social Network Group Decision-Making Based on TrustRank and Personas [J].

Cai, Mei ;

Wang, Yiming ;

Gong, Zaiwu .

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2020, 13 (01) :332-340

← 1 2 3 4 5 6 7 →