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Sipoš, Ruben; Ghosh, Aritra; Joachims, Thorsten

doi:10.1145/2566486.2567998

Cited by 23 publications

(2 citation statements)

References 15 publications

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“…We expect more sophisticated textual features to be necessary to differentiate between meaningful styles of reviews. Sipos et al (2014) found evidence that helpfulness votes are the consequence of judgments of relative quality (i.e., how the review compares to its neighbors) and that aggregate user voting polarity is influenced by the specific review ranking that websites display at any given point in time. To prove this, they collected daily snapshots of the top 50 reviews of 595 Amazon products over a 5 month period.…”

Section: Review Naturementioning

confidence: 99%

Modeling and Prediction of Online Product Review Helpfulness: A Survey

Diaz¹,

Ng²

2018

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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As the popularity of free-form usergenerated reviews in e-commerce and review websites continues to increase, there is a growing need for automatic mechanisms that sift through the vast number of reviews and identify quality content. Online review helpfulness modeling and prediction is a task which studies the factors that determine review helpfulness and attempts to accurately predict it. This survey paper provides an overview of the most relevant work on product review helpfulness prediction and understanding in the past decade, discusses gained insights, and provides guidelines for future research.

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Section: Review Naturementioning

confidence: 99%

Modeling and Prediction of Online Product Review Helpfulness: A Survey

Diaz¹,

Ng²

2018

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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“…An voting patterns application in online content is proposed by Sipos, Ghosh, et al [213]. They explore how users respond to question such as "Was this content helpful?".…”

Section: 2mentioning

confidence: 99%

Influence analysis: A survey of the state-of-the-art

Han¹,

Li²

2018

Mathematical Foundations of Computing

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Online social networks have seen an exponential growth in number of users and activities recently. The rapid proliferation of online social networks provides rich data and infinite possibilities for us to analyze and understand the complex inherent mechanism which governs the evolution of the new online world. This paper summarizes the state-of-art research results on social influence analysis in a broad sense. First, we review the development process of influence analysis in social networks based on several basic conceptions and features in a social aspect. Then the online social networks are discussed. After describing the classical models which simulate the influence spreading progress, we give a bird's eye view of the up-to-date literatures on influence diffusion models and influence maximization approaches. Third, we present the applications including web services, marketing, and advertisement services which based on the influence analysis. At last, we point out the research challenges and opportunities in this area for both industry and academia reference. 201 202 MENG HAN AND YINGSHU LIachieved. Even so, prior to the Internet, quantitative data of social networks were scanty and the further influence analysis in social networks was in the slow-lane. In 2007, Nicholas et al. [47] published their years of research results based on the historical data from the spreading of obesity over 32 years. From the same research filed, David et al. [11] proposed another idea about the spread of obesity in social networks based on the simulations which further considered the group effect in obesity spreading. Both works tried to explore how the influence diffusion in social networks affects obesity. In their model, individuals' influence over each other rely on food intake and physical activities [70]. Since other models consider obesity as a "contagious" phenomenon that can be caught if most social contracts are deemed obese, the interaction of social networks with environmental factors could not be explored. It was not accounted for in the general model where the social networks were proposed as a means to mitigate the obesity epidemic. Many other research results have been obtained recently, such as smoking behavior [48][52], happiness [68], and loneliness [25][117] which spread along a social network over time.At an American high school, Salath et al.[207] obtained high-resolution data of close proximity interactions during a typical day, and their work helps with the reconstruction of a social network for infectious disease transmission by using wireless sensor network technology [246,98]. Through simulations, they showed that targeted immunization using the contact-network data is much more effective than random immunization. Stehle et al. [216] report a similar result like Salath [207] in a French primary school. The team headed by Stehle also provided several public-health implications of infectious diseases by collecting a period of history data from their experiments. By analyzing the real experiments in two ...

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D-HRSP: Dataset of helpful reviews for service providers

Lee

Park

2023

Telematics and Informatics

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Was this review helpful to you?

Cited by 23 publications

References 15 publications

Modeling and Prediction of Online Product Review Helpfulness: A Survey

Modeling and Prediction of Online Product Review Helpfulness: A Survey

Influence analysis: A survey of the state-of-the-art

D-HRSP: Dataset of helpful reviews for service providers

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