This paper examines the effects of review arousal on perceived helpfulness of online reviews, and on consumers’ emotional responses elicited by the reviews. Drawing on emotion theories in psychology and neuroscience, we focus on four emotions – anger, anxiety, excitement, and enjoyment that are common in the context of online reviews. The effects of the four emotions embedded in online reviews ...

Aims and method To examine the usefulness of a cognitive-behavioural therapy-based group intervention, metacognitive training for schizophrenia (MCT), in a 'real-world' clinical setting. In total, 164 participants completed 327 questionnaires at the end of MCT group sessions; rating the perceived usefulness, helpfulness to recovery, change in knowledge and anxiety. Non-parametric statistical te...

BACKGROUND Increasing rates of smoking cessation is one of the most effective measures available to improve population health. To advance the goal of increasing successful cessation at the population level, it is imperative that we understand more about smokers' use of cessation methods, as well as the helpfulness of those methods in real-world experiences of quitting. In this survey of recent ...

Purpose This paper aims to offer a framework explaining how product experience (i.e. think vs feel) and involvement (high low) influence the helpfulness of online reviews. It also reexamined consumer review dimensions help build under different contexts. Design/methodology/approach Data were collected using content analysis on 1,200 customer reviews 12 products from four categories measure rela...

Consumers frequently rely on user-generated product reviews to guide purchasing decisions. Given the everincreasing volume of such reviews and variations in review quality, consumers require assistance to effectively leverage this vast information source. In this paper, we examine to what extent the readability of reviews is a predictor of review helpfulness. Using a supervised classification a...

Review Opinion Diversification (RevOpiD) 2017 is a shared task which is held in International Joint Conference on Natural Language Processing (IJCNLP). The shared task aims at selecting top-k reviews, as a summary, from a set of re-views. There are three subtasks in RevOpiD: helpfulness ranking, representativeness ranking, and exhaustive coverage ranking. This year, our team submitted runs by t...

Reviews keep playing an increasingly important role in the decision process of buying products and booking hotels. However, the large amount of available information can be confusing to users. A more succinct interface, gathering only the most helpful reviews, can reduce information processing time and save effort. To create such an interface in real time, we need reliable prediction algorithms...

Helpful online product reviews, which include massive information, have large impacts on customers? purchasing decisions. In most of e-commerce platforms, the helpfulness reviews are decided by votes from other customers. Making full use these with has enormous commercial value, especially in recommendation. It drives researchers to study technologies about how evaluate review automatically. Al...