网购评语高频词共现网络的结构特征分析
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摘要
网购评语是消费者对网购商品的直接反馈,从中挖掘有价值的知识有助于为商家开展精准化营销和个性化推荐服务、消费者制定购买决策等提供依据。鉴于此,以国内大型综合型电商平台上服装类网购评语为研究对象,对评语分词、筛选高频词、分析高频词之间的共现关系构建高频词共现网络,分析得出网络评语的热点词多个结构特征和评语网络中少数节点对网络的运行起着主导的作用,为网购评语挖掘研究领域提供了按照网购评语高频词共现网络的结构特性对销量的交互影响进行研究的思路。
Consumers' online shopping reviews are consumers' feedback to online shopping. Mining valuable knowledge from massive online shopping reviews will not only provide safeguard for businesses to carry out precision marketing and personalized recommendation services,but also is good for consumers to make purchase decisions. Besides,management departments can use it to establish regulatory strategy. This paper reviewed the clothing online shopping comments on China's large integrated electronic business platform as the object of study,making a participle of the comments,screening high frequency words,analyzing of co-occurrence relationship between the high frequency words in order to structure co-occurrence network of high frequency word. The analysis result shows a number of structural features for the network comments hot words and a few nodes in the comment network play a dominant role in the operation of the network. On the other hand,this paper also provides the study suggestion on the interaction effects of the structure characteristics for the high frequency word co-occurrence network on the sales volume.
Consumers' online shopping reviews are consumers' feedback to online shopping. Mining valuable knowledge from massive online shopping reviews will not only provide safeguard for businesses to carry out precision marketing and personalized recommendation services,but also is good for consumers to make purchase decisions. Besides,management departments can use it to establish regulatory strategy. This paper reviewed the clothing online shopping comments on China's large integrated electronic business platform as the object of study,making a participle of the comments,screening high frequency words,analyzing of co-occurrence relationship between the high frequency words in order to structure co-occurrence network of high frequency word. The analysis result shows a number of structural features for the network comments hot words and a few nodes in the comment network play a dominant role in the operation of the network. On the other hand,this paper also provides the study suggestion on the interaction effects of the structure characteristics for the high frequency word co-occurrence network on the sales volume.
引文
[1]杨铭,祁巍,闫相斌,等.在线商品评论的效用分析研究[J].管理科学学报,2012,15(5):65-75.(Yang Ming,Qi Wei,Yan Xiangbin,et al. Utility analysis for online product review[J]. Journal of Management Sciences in China,2012,15(5):65-75.)
[2]廖成林,蔡春江,李忆.电子商务中在线评论有用性影响因素实证研究[J].软科学,2013,27(5):46-50.(Liao Chenglin,Cai Chunjiang,Li Yi. An empirical study on influence factors of online reviews’helpfulness in E-commerce[J]. Soft Science,2013,27(5):46-50.)
[3]聂卉.基于内容分析的用户评论质量的评价与预测[J].图书情报工作,2014,58(13):83-89.(Nie Hui. Content-oriented evaluation and detection for product reviews[J]. Library and Information Service,2014,58(13):83-89.)
[4]姜巍,张莉,戴翼,等.面向用户需求获取的在线评论有用性分析[J].计算机学报,2013,36(1):119-131.(Jiang Wei,Zhang Li,Dai Yi,et al. Analyzing helpfulness of online reviews for user requirements elicitation[J]. Chinese Journal of Computers,2013,36(1):119-131.)
[5] Titov I,Mc Donald R. Modeling online reviews with multigrain topic models[C]//Proc of the 17th International Conference on World Wide Web. New York:ACM Press,2008:111-120.
[6] Liu Yang,Huang Xiangji,An Aijun,et al. Modeling and predicting the helpfulness of online reviews[C]//Proc of the 8th IEEE International Conference on Data Mining. Washington DC:IEEE Computer Society,2008:443-452.
[7] Cheung C M,Lee M K. What drives consumers to spread electronic word of mouth in online consumer-opinion platforms[J]. Decision Support Systems,2012,53(1):218-225.
[8]闫强,孟跃.在线评论的感知有用性影响因素——基于在线影评的实证研究[J].中国管理科学,2013,21(专辑):126-131.(Yan Qiang,Meng Yue. Factors affecting the perceived usefulness of online reviews:an empirical study based on online file reviews[J].Chinese Journal of Management Science,2013,21(Special Issue):126-131.)
[9]付东普,王刊良.评论回报对在线产品评论的影响研究——社会关系视角[J].管理科学学报,2015,18(11):1-12.(Fu Dongpu,Wang Kanliang. Effects of economic rewards on online product reviews:a perspective of social relations[J]. Journal of Management Sciences in China,2015,18(11):1-12.)
[10]孟美任,丁晟春.虚假商品评论信息发布者行为动机分析[J].情报科学,2013,31(10):100-104.(Meng Meiren,Ding Shengchun. Motivation and behavior of the fraud reviews’publishers[J].Information Science,2013,31(10):100-104.)
[11]王长征,何钐,王魁.网络口碑中追加评论的有用性感知研究[J].管理科学,2015,28(3):102-114.(Wang Changzheng,He Shan,Wang Kui. Research on how additional review affects perceived usefulness of review[J]. Journal of Management Science,2015,28(3):102-114.)
[12]殷国鹏.消费者认为怎样的在线评论更有用?——社会性因素的影响效应[J].管理世界,2012(12):115-124.(Yin Guopeng.How consumers think online reviews are more useful:the influence of social factors[J]. Management World,2012(12):115-124.)
[13]王君珺,闫强.不同热度搜索型产品的在线评论对销量影响的实证研究[J].中国管理科学,2013,21(专辑):406-411.(Wang Junjun,Yan Qiang. An empirical study on impact of online reviews of different product popularity on product sales[J]. Chinese Journal of Management Science,2013,21(Special Issue):406-411.)
[14]李宏,喻葵,夏景波.负面在线评论对消费者网络购买决策的影响:一个实验研究[J].情报杂志,2011,30(5):202-207.(Li Hong,Yu Kui,Xia Jingbo. How negative online reviews affect consumers’online purchasing decision:an empirical study[J]. Journal of Intelligence,2011,30(5):202-207.)
[15]冯娇,姚忠.基于社会学习理论的在线评论信息对购买决策的影响研究[J].中国管理科学,2016,24(9):106-114.(Feng Jiao,Yao Zhong. Consumer-generated reviews based on social learning theory:implications for purchase decision[J]. Chinese Journal of Management Science,2016,24(9):106-114.)
[16] Li Xinxin,Hitt L M. Self-selection and information role of online product reviews[J]. Information Systems Research,2008,19(4):456-474.
[17]Mudambi S M,Schuff D. What makes a helpful online review? A study of customer reviews on Amazon. com[J]. MIS Quarterly,2010,34(1):185-200.
[18] Kwark Y,Chen Jianqing,Raghunathan S. Online product reviews:implications for retailers and competing manufacturers[J]. Information Systems Research,2014,25(1):93-110.
[19]章璇,景奉杰.网购商品的类型对在线冲动性购买行为的影响[J].管理科学,2012,25(3):69-77.(Zhang Xuan,Jing Fengjie. How types of online products affect online impulse buying[J]. Journal of Management Science,2012,25(3):69-77.)
[20]张黎.网民传统的网下购物习惯与其网上购物行为的关联性及其实践意义[J].管理科学,2006,19(2):13-21.(Zhang Li.The implications of consumer off-line shopping behaviors on online shopping behaviors[J]. Journal of Management Science,2006,19(2):13-21.)
[21]龚诗阳,刘霞,赵平.线上消费者评论如何影响产品销量?——基于在线图书评论的实证研究[J].中国软科学,2013(6):171-173.(Gong Shiyang,Liu Xia,Zhao Ping. How do online consumer reviews influence product sales? An empirical study based on online book reviews[J]. China Soft Science,2013(6):171-173.)
[22]石文华,龚雪,张绮,等.在线初次评论与在线追加评论的比较研究[J].管理科学,2016,29(4):45-58.(Shi Wenhua,Gong Xue,Zhang Qi,et al. A comparative study on first-time online reviews and appended online reviews[J]. Journal of Management Science,2016,29(4):45-58.)
[23]杜学美,丁璟妤,谢志鸿,等.在线评论对消费者购买意愿的影响研究[J].管理评论,2016,28(3):173-183.(Du Xuemei,Ding Jingyu,Xie Zhihong,et al. An empirical study on impact of online reviews on consumers’purchasing intention[J]. Management Review,2016,28(3):173-183.)
[24]张紫琼,叶强,李一军.互联网商品评论情感分析研究综述[J].管理科学学报,2010,13(6):84-96.(Zhang Ziqiong,Ye Qiang,Li Yijun. Literature review on sentiment analysis of online product reviews[J]. Journal of Management Sciences in China,2010,13(6):84-96.)
[25]郝媛媛,邹鹏,李一军,等.基于电影面板数据的在线评论情感倾向对销售收入影响的实证研究[J].管理评论,2009,21(10):95-103.(Hao Yuanyuan,Zou Peng,Li Yijun,et al. An empirical study on influence of emotional tendency in online reviews on sales revenue based on movie panel data[J]. Management Review,2009,21(10):95-103.)
[26]李永忠,胡思琪.基于HowNet和PAT树的网购评语情感分析[J].图书情报研究,2016(3):66-70,65.(Li Yongzhong,Hu Siqi. Sentiment analysis of the comments on online shopping based on HowNet and PAT tree[J]. Library and Information Studies,2016(3):66-70,65.)
[27] Hu Minqing,Liu Bing. Mining and summarizing customer reviews[C]//Proc of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York:ACM Press,2004:168-171.
[28]王洪伟,郑丽娟,尹裴,等.基于句子级情感的中文网络评论的情感极性分类[J].管理科学学报,2013,16(9):64-74.(Wang Hongwei,Zheng Lijuan,Yin Pei,et al. Classification of sentimental polarity for Chinese online reviews based on sentence level sentiment[J]. Journal of Management Sciences in China,2013,16(9):64-74.)
[29]王伟,王洪伟,孟园.协同过滤推荐算法研究:考虑在线评论情感倾向[J].系统工程理论与实践,2014,34(12):3238-3249.(Wang Wei,Wang Hongwei,Meng Yuan. The collaborative filtering recommendation based on sentiment analysis of online reviews[J].Systems Engineering-Theory&Practice,2014,34(12):3238-3249.)
[30]蒋建洪,赵嵩正,罗玫.词典与统计方法结合的中文分词模型研究及应用[J].计算机工程与设计,2012,33(1):387-391.(Jiang Jianhong,Zhao Songzheng,Luo Mei. Analysis and application of Chinese word segmentation model which consist of dictionary and statistics method[J]. Computer Engineering and Design,2012,33(1):387-391.)
[31]张敏,王春红.基于统计方法的Web新词分词方法研究[J].计算机工程与科学,2010,32(5):133-135.(Zhang Min,Wang Chunhong. Study on new words of Web based on statistical word segmentation[J]. Computer Engineering and Science,2010,32(5):133-135.)
[32]黄德根,马玉霞,杨元生.基于互信息的中文姓名识别方法[J].大连理工大学学报,2004,44(5):744-748.(Huang Degen,Ma Yuxia,Yang Yuansheng. Chinese names identification based on mutual information[J]. Journal of Dalian University of Technology,2004,44(5):744-748.)
[33]Watts D J,Strogatz S H. Collective dynamics of‘small-world’networks[J]. Nature,1998,393(6684):440-442.
[34]Newman M E J. The structure and function of complex networks[J].SIAM Review,2003,45(2):167-256.
[35]Zhou Shi,Mondragon R J. The rich-club phenomenon in the Internet topology[J]. IEEE Communications Letters,2004,8(3):180-182.
[36]Girvan M,Newman M E J. Community structure in social and biological networks[J]. Proceedings of National Academy of Sciences of the USA,2002,99(12):7821-7826.
[2]廖成林,蔡春江,李忆.电子商务中在线评论有用性影响因素实证研究[J].软科学,2013,27(5):46-50.(Liao Chenglin,Cai Chunjiang,Li Yi. An empirical study on influence factors of online reviews’helpfulness in E-commerce[J]. Soft Science,2013,27(5):46-50.)
[3]聂卉.基于内容分析的用户评论质量的评价与预测[J].图书情报工作,2014,58(13):83-89.(Nie Hui. Content-oriented evaluation and detection for product reviews[J]. Library and Information Service,2014,58(13):83-89.)
[4]姜巍,张莉,戴翼,等.面向用户需求获取的在线评论有用性分析[J].计算机学报,2013,36(1):119-131.(Jiang Wei,Zhang Li,Dai Yi,et al. Analyzing helpfulness of online reviews for user requirements elicitation[J]. Chinese Journal of Computers,2013,36(1):119-131.)
[5] Titov I,Mc Donald R. Modeling online reviews with multigrain topic models[C]//Proc of the 17th International Conference on World Wide Web. New York:ACM Press,2008:111-120.
[6] Liu Yang,Huang Xiangji,An Aijun,et al. Modeling and predicting the helpfulness of online reviews[C]//Proc of the 8th IEEE International Conference on Data Mining. Washington DC:IEEE Computer Society,2008:443-452.
[7] Cheung C M,Lee M K. What drives consumers to spread electronic word of mouth in online consumer-opinion platforms[J]. Decision Support Systems,2012,53(1):218-225.
[8]闫强,孟跃.在线评论的感知有用性影响因素——基于在线影评的实证研究[J].中国管理科学,2013,21(专辑):126-131.(Yan Qiang,Meng Yue. Factors affecting the perceived usefulness of online reviews:an empirical study based on online file reviews[J].Chinese Journal of Management Science,2013,21(Special Issue):126-131.)
[9]付东普,王刊良.评论回报对在线产品评论的影响研究——社会关系视角[J].管理科学学报,2015,18(11):1-12.(Fu Dongpu,Wang Kanliang. Effects of economic rewards on online product reviews:a perspective of social relations[J]. Journal of Management Sciences in China,2015,18(11):1-12.)
[10]孟美任,丁晟春.虚假商品评论信息发布者行为动机分析[J].情报科学,2013,31(10):100-104.(Meng Meiren,Ding Shengchun. Motivation and behavior of the fraud reviews’publishers[J].Information Science,2013,31(10):100-104.)
[11]王长征,何钐,王魁.网络口碑中追加评论的有用性感知研究[J].管理科学,2015,28(3):102-114.(Wang Changzheng,He Shan,Wang Kui. Research on how additional review affects perceived usefulness of review[J]. Journal of Management Science,2015,28(3):102-114.)
[12]殷国鹏.消费者认为怎样的在线评论更有用?——社会性因素的影响效应[J].管理世界,2012(12):115-124.(Yin Guopeng.How consumers think online reviews are more useful:the influence of social factors[J]. Management World,2012(12):115-124.)
[13]王君珺,闫强.不同热度搜索型产品的在线评论对销量影响的实证研究[J].中国管理科学,2013,21(专辑):406-411.(Wang Junjun,Yan Qiang. An empirical study on impact of online reviews of different product popularity on product sales[J]. Chinese Journal of Management Science,2013,21(Special Issue):406-411.)
[14]李宏,喻葵,夏景波.负面在线评论对消费者网络购买决策的影响:一个实验研究[J].情报杂志,2011,30(5):202-207.(Li Hong,Yu Kui,Xia Jingbo. How negative online reviews affect consumers’online purchasing decision:an empirical study[J]. Journal of Intelligence,2011,30(5):202-207.)
[15]冯娇,姚忠.基于社会学习理论的在线评论信息对购买决策的影响研究[J].中国管理科学,2016,24(9):106-114.(Feng Jiao,Yao Zhong. Consumer-generated reviews based on social learning theory:implications for purchase decision[J]. Chinese Journal of Management Science,2016,24(9):106-114.)
[16] Li Xinxin,Hitt L M. Self-selection and information role of online product reviews[J]. Information Systems Research,2008,19(4):456-474.
[17]Mudambi S M,Schuff D. What makes a helpful online review? A study of customer reviews on Amazon. com[J]. MIS Quarterly,2010,34(1):185-200.
[18] Kwark Y,Chen Jianqing,Raghunathan S. Online product reviews:implications for retailers and competing manufacturers[J]. Information Systems Research,2014,25(1):93-110.
[19]章璇,景奉杰.网购商品的类型对在线冲动性购买行为的影响[J].管理科学,2012,25(3):69-77.(Zhang Xuan,Jing Fengjie. How types of online products affect online impulse buying[J]. Journal of Management Science,2012,25(3):69-77.)
[20]张黎.网民传统的网下购物习惯与其网上购物行为的关联性及其实践意义[J].管理科学,2006,19(2):13-21.(Zhang Li.The implications of consumer off-line shopping behaviors on online shopping behaviors[J]. Journal of Management Science,2006,19(2):13-21.)
[21]龚诗阳,刘霞,赵平.线上消费者评论如何影响产品销量?——基于在线图书评论的实证研究[J].中国软科学,2013(6):171-173.(Gong Shiyang,Liu Xia,Zhao Ping. How do online consumer reviews influence product sales? An empirical study based on online book reviews[J]. China Soft Science,2013(6):171-173.)
[22]石文华,龚雪,张绮,等.在线初次评论与在线追加评论的比较研究[J].管理科学,2016,29(4):45-58.(Shi Wenhua,Gong Xue,Zhang Qi,et al. A comparative study on first-time online reviews and appended online reviews[J]. Journal of Management Science,2016,29(4):45-58.)
[23]杜学美,丁璟妤,谢志鸿,等.在线评论对消费者购买意愿的影响研究[J].管理评论,2016,28(3):173-183.(Du Xuemei,Ding Jingyu,Xie Zhihong,et al. An empirical study on impact of online reviews on consumers’purchasing intention[J]. Management Review,2016,28(3):173-183.)
[24]张紫琼,叶强,李一军.互联网商品评论情感分析研究综述[J].管理科学学报,2010,13(6):84-96.(Zhang Ziqiong,Ye Qiang,Li Yijun. Literature review on sentiment analysis of online product reviews[J]. Journal of Management Sciences in China,2010,13(6):84-96.)
[25]郝媛媛,邹鹏,李一军,等.基于电影面板数据的在线评论情感倾向对销售收入影响的实证研究[J].管理评论,2009,21(10):95-103.(Hao Yuanyuan,Zou Peng,Li Yijun,et al. An empirical study on influence of emotional tendency in online reviews on sales revenue based on movie panel data[J]. Management Review,2009,21(10):95-103.)
[26]李永忠,胡思琪.基于HowNet和PAT树的网购评语情感分析[J].图书情报研究,2016(3):66-70,65.(Li Yongzhong,Hu Siqi. Sentiment analysis of the comments on online shopping based on HowNet and PAT tree[J]. Library and Information Studies,2016(3):66-70,65.)
[27] Hu Minqing,Liu Bing. Mining and summarizing customer reviews[C]//Proc of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York:ACM Press,2004:168-171.
[28]王洪伟,郑丽娟,尹裴,等.基于句子级情感的中文网络评论的情感极性分类[J].管理科学学报,2013,16(9):64-74.(Wang Hongwei,Zheng Lijuan,Yin Pei,et al. Classification of sentimental polarity for Chinese online reviews based on sentence level sentiment[J]. Journal of Management Sciences in China,2013,16(9):64-74.)
[29]王伟,王洪伟,孟园.协同过滤推荐算法研究:考虑在线评论情感倾向[J].系统工程理论与实践,2014,34(12):3238-3249.(Wang Wei,Wang Hongwei,Meng Yuan. The collaborative filtering recommendation based on sentiment analysis of online reviews[J].Systems Engineering-Theory&Practice,2014,34(12):3238-3249.)
[30]蒋建洪,赵嵩正,罗玫.词典与统计方法结合的中文分词模型研究及应用[J].计算机工程与设计,2012,33(1):387-391.(Jiang Jianhong,Zhao Songzheng,Luo Mei. Analysis and application of Chinese word segmentation model which consist of dictionary and statistics method[J]. Computer Engineering and Design,2012,33(1):387-391.)
[31]张敏,王春红.基于统计方法的Web新词分词方法研究[J].计算机工程与科学,2010,32(5):133-135.(Zhang Min,Wang Chunhong. Study on new words of Web based on statistical word segmentation[J]. Computer Engineering and Science,2010,32(5):133-135.)
[32]黄德根,马玉霞,杨元生.基于互信息的中文姓名识别方法[J].大连理工大学学报,2004,44(5):744-748.(Huang Degen,Ma Yuxia,Yang Yuansheng. Chinese names identification based on mutual information[J]. Journal of Dalian University of Technology,2004,44(5):744-748.)
[33]Watts D J,Strogatz S H. Collective dynamics of‘small-world’networks[J]. Nature,1998,393(6684):440-442.
[34]Newman M E J. The structure and function of complex networks[J].SIAM Review,2003,45(2):167-256.
[35]Zhou Shi,Mondragon R J. The rich-club phenomenon in the Internet topology[J]. IEEE Communications Letters,2004,8(3):180-182.
[36]Girvan M,Newman M E J. Community structure in social and biological networks[J]. Proceedings of National Academy of Sciences of the USA,2002,99(12):7821-7826.