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Review helpfulness is attracting increasing attention of practitioners and academics. It helps in reducing risks and uncertainty faced by users in online shopping. This study examines uninvestigated variables by looking at not only the review characteristics but also important indicators of reviewers. Several significant review content and two reviewer variables are proposed and an effective review helpfulness prediction model is built using stochastic gradient boosting learning method. This study derived a mechanism to extract novel review content variables from review text. Six popular machine learning models and three real-life Amazon review data sets are used for analysis. Our results are robust to several product categories and along three Amazon review data sets. The results show that review content variables deliver the best performance as compared to the reviewer and state-of-the-art baseline as a standalone model. This study finds that reviewer helpfulness per day and syllables in review text strongly relates to review helpfulness. Moreover, the number of space, aux verb, drives words in review text and productivity score of a reviewer are also effective predictors of review helpfulness. The findings will help customers to write better reviews, help retailers to manage their websites intelligently and aid customers in their product purchasing decisions. 相似文献
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The use of the internet and social media have changed consumer behavior and the ways in which companies conduct their business. Social and digital marketing offers significant opportunities to organizations through lower costs, improved brand awareness and increased sales. However, significant challenges exist from negative electronic word-of-mouth as well as intrusive and irritating online brand presence. This article brings together the collective insight from several leading experts on issues relating to digital and social media marketing. The experts’ perspectives offer a detailed narrative on key aspects of this important topic as well as perspectives on more specific issues including artificial intelligence, augmented reality marketing, digital content management, mobile marketing and advertising, B2B marketing, electronic word of mouth and ethical issues therein. This research offers a significant and timely contribution to both researchers and practitioners in the form of challenges and opportunities where we highlight the limitations within the current research, outline the research gaps and develop the questions and propositions that can help advance knowledge within the domain of digital and social marketing. 相似文献
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Youngtae Choi 《Journal of Intercultural Communication Research》2019,48(3):292-313
This study explores how horizontal/vertical individualism and collectivism (HVIC) orientations influence electronic word-of-mouth (eWOM) (i.e., opinion leadership and opinion seeking) in social media. Online survey panel data through Amazon MTurk were collected from American social media users to address the research purpose. The results, using the structural equation modeling, show that the paths from horizontal individualism to opinion leadership, vertical individualism to opinion leadership and opinion seeking, horizontal collectivism to opinion leadership, and vertical collectivism to opinion leadership and opinion seeking were significant. This study provides theoretical and managerial implications regarding the influence of HVIC orientations on eWOM in social media. 相似文献
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以网络口碑传播理论和相关研究为基础进行文献分析,提出研究假设,构建理论模型,并以泉州7家高校810名大学生作为研究对象进行问卷调查。运用结构方程模型(SEM)方法进行验证,得出网络口碑的质量、时效性、极性、强度与体育用品购买决策之间呈现正向相关关系。最后,依据实证研究结论提出重视网络口碑的营造,提高网络口碑质量,及时更新网络口碑信息,注重网络口碑极性以及关注网络口碑的强度的管理建议。 相似文献
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Electronic word of mouth (eWOM) is prominent and abundant in consumer domains. Both consumers and product/service providers need help in understanding and navigating the resulting information spaces, which are vast and dynamic. The general tone or polarity of reviews, blogs or tweets provides such help. In this paper, we explore the viability of automatic sentiment analysis (SA) for assessing the polarity of a product or a service review. To do so, we examine the potential of the major approaches to sentiment analysis, along with star ratings, in capturing the true sentiment of a review. We further model contextual factors (specifically, product type and review length) as two moderators affecting SA accuracy. The results of our analysis of 900 reviews suggest that different tools representing the main approaches to SA display differing levels of accuracy, yet overall, SA is very effective in detecting the underlying tone of the analyzed content, and can be used as a complement or an alternative to star ratings. The results further reveal that contextual factors such as product type and review length, play a role in affecting the ability of a technique to reflect the true sentiment of a review. 相似文献
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《International Journal of Information Management》2017,37(3):202-213
Due to the proliferation of Web 2.0 technology, e-commerce has evolved into social commerce. In this social commerce era, consumers are increasingly dependent on each other and look for social support (informational and emotional) online even before making purchases. This study examines the content of consumer reviews, a fundamental construct of social commerce. Topics expressed in consumer reviews (collected from Amazon.com) are explored using a machine learning technique (i.e. latent semantic analysis). This study documents the thematic differences between positive and negative reviews and finds that negative reviews report service-related failures while positive reviews relate more to the product, among other things. Next, the informational support aspect of social commerce is explored by identifying the topics expressed in reviews that are helpful in purchase decisions. The findings demonstrate that potential customers (i.e. those who would like to purchase a product in the near future and currently are reading reviews with the intention to decide whether or not to buy that product) find the negative reviews containing service failure information and the positive reviews containing information on core functionalities, technical aspects, and aesthetics to be more helpful. Theoretical and managerial implications are discussed. 相似文献
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Social media influencers (SMIs) as significant stakeholders are increasingly collaborating with brands to cultivate marketing campaigns. However, literature concerning the narrative strategies used by SMIs to create electronic word-of-mouth (eWOM) to introduce brands and products remains under-theorised. This research takes a theoretical perspective of marketing communication, advances the eWOM theory to develop SMIs’ eWOM model as the theoretical lens, and adopts semiotic and rhetorical approaches to identify SMIs’ narrative strategies to create eWOM to promote brands and products to consumers. By conducting a netnographic study to observe fashion bloggers’ messages concerning Western luxury brands on Chinese social media, this research identified six distinct narrative strategies that are different in linking the purpose of eWOM, assigning brands with roles in eWOM, representing the meanings associated with brands, and using modes of persuasion to convince consumers to accept these meanings. This research also proposes a model to illustrate the structure of SMIs’ narrative strategies. The results of this research have implications for the advancement of social media marketing theories and provide a foundation for future development of knowledge regarding SMIs’ narrative strategies. 相似文献
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[目的/意义]以传播渠道为调节变量,探究网络口碑的传播者特性和传播内容特性对消费者图书购买意愿的影响机理,为图书出版行业相关主体进行口碑营销提供参考借鉴。[方法/过程]基于信息传播理论,以传播渠道为调节变量,构建网络口碑对消费者图书购买意愿影响的理论模型。通过问卷调查收集数据,使用回归分析方法厘清网络口碑与消费者图书购买意愿的关系,并实证检验相关因素的影响效应。[结果/结论]传播内容（信息）特性对消费者图书购买意愿具有直接的显著影响。传播者（信源）特性既存在对购买意愿的直接显著影响,也存在以传播内容特性为中介的间接显著影响。传播渠道（信道）的调节效应显著,其中对传播者特性与购买意愿的调节中,文化推广式平台的调节效应最大,其次为营销式平台,自由讨论式平台最小;对传播内容与购买意愿的调节中,文化推广式平台的调节效应仍然最大,自由讨论式平台略低,而营销式平台最小。最后,从传播内容的设计、名人效应的发挥和营销平台的选择与建设3个方面分别提出了建议。 相似文献
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伴随着社交媒体的迅速发展,在线口碑传播的作用也与日俱增。对295个大学生样本进行分析,验证了大学生在线口碑传播行为对购买意向的影响作用,发现了顾客体验在在线口碑传播行为三个维度与购买意向的关系中的中介作用。其中,顾客体验在信息搜寻与购买意向之间的关系中所发挥的中介作用最为显著。基于研究结果,可以从培育领袖、塑造氛围、积极管理、和优化平台提供对策和建议。 相似文献
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