[1] 商务部电子商务和信息化司. 中国电子商务报告2019[R]. 北京: 商务部电子商务和信息化司, 2020.
[2] 赵曙光. 网络评论蓝皮书: 中国网络评论发展报告(2019)[R]. 北京: 南京大学, 2019.
[3] MUDAMBI S M, SCHUFF D. Research note: what makes a helpful online review? a study of customer reviews on amazon. com[J]. MIS Quarterly, 2010, 34(1): 185-200.doi:10.2307/20721420
[4] 郝媛媛, 叶强, 李一军. 基于影评数据的在线评论有用性影响因素研究[J]. 管理科学学报, 2010, 13(8): 78-88.
[5] LIU Z, PARK S. What makes a useful online review? Implication for travel product websites[J]. Tourism Management, 2015, 47: 140-151.doi:10.1016/j.tourman.2014.09.020
[6] MA Y, XIANG Z, DU Q, et al. Effects of user-provided photos on hotel review helpfulness: an analytical approach with deep leaning[J]. International Journal of Hospitality Management, 2018, 71: 120-131.doi:10.1016/j.ijhm.2017.12.008
[7] SIERING M, MUNTERMANN J, RAJAGOPALAN B. Explaining and predicting online review helpfulness: the role of content and reviewer-related signals[J]. Decision Support Systems, 2018, 108: 1-12.doi:10.1016/j.dss.2018.01.004
[8] SUN X, HAN M, FENG J. Helpfulness of online reviews: examining review informativeness and classification thresholds by search products and experience products[J/OL]. Decision Support Systems, 2019, 124: 113099.https://www.doc88.com/p-90129299555910.html.
[9] ZHOU Y, YANG S, LI Y, et al. Does the review deserve more helpfulness when its title resembles the content? locating helpful reviews by text mining[J]. Information Processing & Management, 2020, 57(2): 102179.
[10] LI X, WU C, MAI F. The effect of online reviews on product sales: a joint sentiment-topic analysis[J]. Information & Management, 2019, 56(2): 172-184.
[11] SUN M. How does the variance of product ratings matter?[J]. Management Science, 2012, 58: 696-707.doi:10.1287/mnsc.1110.1458
[12] ABDI A, SHAMSUDDIN S M, HASAN S, et al. Deep learning-based sentiment classification of evaluative text based on Multi-feature fusion[J]. Information Processing & Management, 2019, 56(4): 1245-1259.
[13] 刘通, 张聪, 吴鸣远. 在线评论中基于边界平均信息熵的产品特征提取算法[J]. 系统工程理论与实践, 2016, 36(9): 2416-2423.doi:10.12011/1000-6788(2016)09-2416-08
[14] HEYDARI A, TAVAKOLI M, SALIM N. Detection of fake opinions using time series[J]. Expert Systems with Applications, 2016, 58: 83-92.doi:10.1016/j.eswa.2016.03.020
[15] 郝玫, 马建峰. 在线评论中基于动态窗口提取特征观点对的产品推荐模型[J]. 系统工程理论与实践, 2018, 38(9): 2363-2375.doi:10.12011/1000-6788(2018)09-2363-13
[16] MORENTE-MOLINERA J, KOU G, SAMOUYLOV K, et al. Carrying out consensual group decision making processes under social networks using sentiment analysis over comparative expressions[J]. Knowledge-Based Systems, 2018, 165: 335-345.
[17] LIU Y, JIANG C, ZHAO H. Using contextual features and multi-view ensemble learning in product defect identification from online discussion forums[J]. Decision Support Systems, 2018, 105: 1-12.doi:10.1016/j.dss.2017.10.009
[18] 黄卫来, 潘晓波. 在线商品评价信息有用性模型研究: 纳入应用背景因素的信息采纳扩展模型[J]. 图书情报工作, 2014, 58(S1): 141-151.
[19] ESLAMI S P, GHASEMAGHAEI M, HASSANEIN K. Which online reviews do consumers find most helpful? a multi-method investigation[J]. Decision Support Systems, 2018, 113: 32-42.doi:10.1016/j.dss.2018.06.012
[20] 艾时钟, 曾鑫. 基于Ebay评论数据中的情感总量与信息熵对评论有用性的影响[J]. 软科学, 2019, 33(7): 129-132.doi:10.13956/j.ss.1001-8409.2019.07.21
[21] SRIVASTAVA V, KALRO A D. Enhancing the helpfulness of online consumer reviews: the role of latent (content) factors[J]. Journal of Interactive Marketing, 2019, 48: 33-50.doi:10.1016/j.intmar.2018.12.003
[22] GHOSE A, IPEIROTIS P G. Estimating the helpfulness and economic impact of product reviews: mining text and reviewer characteristics[J]. IEEE Transactions on Knowledge and Data Engineering, 2011, 23(10): 1498-1512.doi:10.1109/TKDE.2010.188
[23] YANG S, ZHOU Y, YAO J, et al. Understanding online review helpfulness in omnichannel retailing[J]. Industrial Management & Data Systems, 2019, 119(8): 1565-1580.
[24] CHATTERJEE S. Drivers of helpfulness of online hotel reviews: a sentiment and emotion mining approach[J/OL]. International Journal of Hospitality Management, 2020, 85: 102356. https://www.sciencedirect.com/science/article/abs/pii/S0278431919300052.
[25] MITRA S, JENAMANI M. Helpfulness of online consumer reviews: a multi-perspective approach[J/OL]. Information Processing & Management, 2021, 58(3): 102538. https://www.sciencedirect.com/science/article/abs/pii/S0306457321000467.
[26] CAO Q, DUAN W, GAN Q. Exploring determinants of voting for the "helpfulness" of online user reviews: a text mining approach[J]. Decision Support Systems, 2011, 50(2): 511-521.doi:10.1016/j.dss.2010.11.009
[27] KUAN K K, HUI K, PRASARNPHANICH P, et al. What makes a review voted? an empirical investigation of review voting in online review systems[J]. Journal of the Association for Information Systems, 2015, 16(1): 47-71.
[28] HONG H, XU D, WANG G A, et al. Understanding the determinants of online review helpfulness: a meta-analytic investigation[J]. Decision Support Systems, 2017, 102: 1-11.doi:10.1016/j.dss.2017.06.007
[29] CHEUNG C M K, LEE M K O, RABJOHN N. The impact of electronic word-of-mouth[J]. Internet Research, 2008, 18(3): 229-247.doi:10.1108/10662240810883290
[30] 袁海霞, 陈俊, 白琳. 电商平台商品标题优化的有效性及其杠杆机制[J]. bob手机在线登陆学报(社会科学版), 2019(2): 116-126.doi:10.15918/j.jbitss1009-3370.2019.1205
[31] ZHANG Y, LIN Z. Predicting the helpfulness of online product reviews: a multilingual approach[J]. Electronic Commerce Research and Applications, 2018, 27: 1-10.doi:10.1016/j.elerap.2017.10.008
[32] XIANG Z, DU Q, MA Y, et al. A comparative analysis of major online review platforms: implications for social media analytics in hospitality and tourism[J]. Tourism Management, 2017, 58: 51-65.doi:10.1016/j.tourman.2016.10.001
[33] 王月辉, 刘爽, 唐胜男, 等. B2C社交电商平台顾客在线购物体验质量测量与实证研究[J]. bob手机在线登陆学报(社会科学版), 2021, 23(3): 71-85.doi:10.15918/j.jbitss1009-3370.2021.2772
[34] YIN D, MITRA S, ZHANG H. Research note—when do consumers value positive vs. negative reviews? an empirical investigation of confirmation bias in online word of mouth[J]. Information Systems Research, 2016, 27(1): 131-144.doi:10.1287/isre.2015.0617
[35] DAVIS J M, AGRAWAL D. Understanding the role of interpersonal identification in online review evaluation: an information processing perspective[J]. International Journal of Information Management, 2018, 38(1): 140-149.doi:10.1016/j.ijinfomgt.2017.08.001
[36] LEE P, HU Y, LU K. Assessing the helpfulness of online hotel reviews: a classification-based approach[J]. Telematics and Informatics, 2018, 35(2): 436-445.doi:10.1016/j.tele.2018.01.001
[37] TSAI C, CHEN K, HU Y, et al. Improving text summarization of online hotel reviews with review helpfulness and sentiment[J/OL]. Tourism Management, 2020, 80: 104122. https://www.sciencedirect.com/science/article/abs/pii/S0261517720300480.
[38] FILIERI R, RAGUSEO E, VITARI C. When are extreme ratings more helpful? empirical evidence on the moderating effects of review characteristics and product type[J]. Computers in Human Behavior, 2018, 88: 134-142.doi:10.1016/j.chb.2018.05.042
[39] SUSSMAN S W, SIEGAL W S. Informational influence in organizations: an integrated approach to knowledge adoption[J]. Information Systems Research, 2003, 14(1): 47-65.doi:10.1287/isre.14.1.47.14767
[40] 汪旭晖, 聂可昱, 陈荣. “解释行为”还是“解释反应”? 怎样的在线评论更有用: 基于解释类型的在线评论对消费者购买决策的影响及边界条件[J]. 南开管理评论, 2017, 20(4): 27-37.
[41] 李嘉, 张朋柱, 刘璇. 更丰富的媒介效果一定更好吗?网络口碑对购物决策的影响研究[J]. 信息系统学报, 2014(1): 31-46.
[42] SALEHAN M, KIM D J. Predicting the performance of online consumer reviews: a sentiment mining approach to big data analytics[J]. Decision Support Systems, 2016, 81: 30-40.doi:10.1016/j.dss.2015.10.006
[43] RYU K, LEE H R, GON KIM W. The influence of the quality of the physical environment, food, and service on restaurant image, customer perceived value, customer satisfaction, and behavioral intentions[J]. International Journal of Contemporary Hospitality Management, 2012, 24(2): 200-223.doi:10.1108/09596111211206141
[44] 肖轶楠, 李江敏. 基于在线点评的高端度假酒店宾客感知服务质量研究: 以悦榕庄酒店为例[J]. 价值工程, 2016, 35(3): 192-193.
[45] NAMKUNG Y, SOOCHEONG S J. Are highly satisfied restaurant customers really different? a quality perception perspective. [J]. International Journal of Contemporary Hospitality Management, 2008, 20(2): 142-155.doi:10.1108/09596110810852131
[46] 严建援, 张丽, 张蕾. 电子商务中在线评论内容对评论有用性影响的实证研究[J]. 情报科学, 2012, 30(5): 713-716.doi:10.13833/j.cnki.is.2012.05.020
[47] WANG X, TANG L R, KIM E. More than words: do emotional content and linguistic style matching matter on restaurant review helpfulness?[J]. International Journal of Hospitality Management, 2019, 77: 438-447.doi:10.1016/j.ijhm.2018.08.007
[48] 苗蕊, 徐健. 评分不一致性对在线评论有用性的影响: 归因理论的视角[J]. 中国管理科学, 2018, 26(5): 178-186.
[49] 苗蕊. 在线评论有用性研究综述[J]. 中国管理信息化, 2014, 17(18): 126-128.doi:10.3969/j.issn.1673-0194.2014.18.077
Baidu
map