Research on Online Word-of-mouth Sentiment Analysis and Attribute Extraction Based on Deep Learning

Online word-of-mouth content mining is of great significance to product, service improvement and demand prediction of online marketing enterprises. However, most studies have focused on the identification of the sentiment tendency of online word-of-mouth, and lack of text content mining for online word-of-mouth, especially negative word-of-mouth. This paper introduces deep learning into online word-of-mouth sentiment tendency analysis and negative word-of-mouth word attribute feature extraction, and builds an online word-of-mouth sentiment tendency analysis and attribute extraction model based on LSTM deep learning algorithm. The model was trained and tested through online word-of-mouth data of a fashion apparel e-commerce company. The results show that the LSTM model has a good effect on sentiment analysis and negative word-of-mouth attribute feature extraction. Through comparative experiments, it is shown that the model has a better effect than the traditional machine learning methods (SVM, Naive Bayes) in the analysis of sentiment tendency

Word of Mouth Advertising, Credibility and Learning in Networks

Social networks representing the pattern of social interactions - who talks to or who observes whom- play a crucial role as a medium for the spread of information, ideas, diseases, products. Someone in the population may struck with an infection or may adopt a new technology, and it can then either die out quickly or spread throughout the population, depending possibly on the location of the initial appearance, the structure of the network - for instance, how dense it is. The dynamics of adoption -the extent to which individuals are in uenced by their neighbours, the impact of "word of-mouth" communication- also plays a role in determining the speed of diffusion. Given the large range of contexts in which social learning is important, it is not surprising that researchers from various disciplines have studied processes of diffusion from a variety of perspectives.

The Influence of Word of Mouth Communication Towards Brand Image of Iphone on Student of Political Science and Social Science Faculty University of Riau

This research starts on the behavioristik learning theory, This theory assumes that human behavior is a process of learning. This means, if a response given by a person to a stimulus is true and he knew it, then our satisfaction will be achieved and the Association strengthened. In this research word of mouth communication looking at how a recipient of word of mouth communication of influence can lead to brand image iphone, word of mouth communication that occurs naturally and simple unwittingly introduced the iphone. The purpose of this research is to determine, whether there is an influence of word of mouth communication towards brand image of iphone on student of Political Science and Social Science Faculty University of Riau.The method used in this study is a quantitative method of explanation. Data collection techniques in this study using a questionnaire. The number of samples for this study were 166 respondents. Sampling using Accidental sampling and using propotional sampling techniques. To determine how much influence these two variables, the researchers used a simple linear regression analysis. Questionnaire for data processing, carried out using the program Statistics Product And Service Solutions (SPSS) version of Windows 23.Results of research on the influence of word of mouth communication towards brand image of Iphone on student of political science and social science faculty university of Riau regression coefficient values obtained in this study is Y = 4,682 + 0,523 X with significance level 0,006 that smaller than α = 0.05. This means that there is the influence of word of mouth communication towards brand image of iphone on student of political science and social science faculty university of Riau of 52,6% and in the category of influential medium. The percentages indicate that the word of mouth communication towards brand image of iphone wit H0 is rejected and Ha accepted

Sensegiving Word-of-Mouth and Collective Sensemaking About Epistemic Objects

Using theories of sensegiving and sensemaking, I explore how people engage in word-of-mouth about stocks, which are conceptualized as epistemic objects. I draw on netnographic and interview data related to an online investment community, and find that people employ five broad types of word-of-mouth strategies – framing, cuing, connecting, action facilitating, and unsettling – in giving sense about epistemic objects. I also identify the ways in which audiences respond to this form of word-of-mouth, as a part of a collective sensemaking process, and find that their responses pertain to the speaker, the account, as well as their own behavior. Finally, I develop propositions that describe the relationships between sensegiving word-of-mouth strategies and the responses they elicit. This research makes a number of conceptual contributions. It develops the concept of discursive response, an important component of networked word-of-mouth and a manifestation of engagement, and identifies the word-of-mouth strategies associated with higher volumes and types of discursive response. It generates knowledge about word-of-mouth processes. It also provides learning about collective sensemaking and sensegiving. Along with these contributions, this research offers important insights for managers and public policy makers, such as how to elicit online engagement and assist in the collective sensemaking process

An Empirical Study of Peer Influence on User Attitudes, Behavior, and Performance

User attitudes, behavior, and performance have been studied by many researchers, yet we do not have a very complete understanding of their determinants. Word-of-mouth communication is described in this study as one potentially powerful influence on those outcomes. A deception experiment tested the effects of word-of-mouth communication on novices engaged in a learning task. It was hypothesized that negative communication would diminish attitudes, behaviors and behavioral intentions, and performance on material retention as well as task accuracy. The results provided evidence of the effects of word-of- mouth communication on attitudes, behavioral intentions, and software test performance, but failed to provide evidence that actual behavior or task performance are affected by such communication

Android Smartphone Among Young People

This study aims to determine purchasing decisions among young people who need their daily life is still filled by the lord yes. Android smartphones among young people are still included in the category of expensive items. The sample used is young people who are still learning and have no income. Consumers in determining the decision to purchase products are influenced by including price perceptions, product features, and word of mouth. Consumer complaints about price perceptions are caused by Android smartphones perceived to be more expensive. Price perception is related to how price information is understood entirely by consumers and gives a deep meaning to them, three indicators namely: Price conformity to product quality, Price conformity to benefits and Competitive prices. Product features are elements of a product that are considered important by consumers and are used as the basis for making a purchasing decision, researchers use four indicators, namely: Diversity of Features, Quality of Features, Importance of Features and Completeness of Features. Word of Mouth or WOM is the act of providing any information related to the product by consumers to other consumers. there are three indicators of Word of Mouth, namely: Word of Mouth Organic, Word of Mouth Amplified and Word of Mouth Marketing. The purchase decision is a decision as the choice of an action of two or more alternative choices, there are six indicators namely: Product choice, Brand choice, Time choice, Store choice, Choice of amount and Choice of payment. From the results of this study it was found that the influence of Price Perception (X₁), Product Features (X₂) and Word of Mouth (X₃) on Purchasing Decisions (Y) had a very strong and positive effect because when young people whose financial needs were still met from his parents or young people who have not worked is largely determined by the variable Price Perception (X ₁), Product Features (X ₂) and Word of Mouth (X ₃) together or simultaneously affect the Purchase Decision (Y) of an android smartphone

Impact of Social Interaction on Live-streaming Shopping Websites

Social interaction (via electronic word of mouth and observational learning) is an essential factor for successful online commerce. The new technology of live-streaming changes how social interaction affects consumers. This ongoing research investigates how instant electronic word of mouth and observational learning influence consumers’ perceptions of a live-streaming shopping website. This study also regards the perceived credibility of the seller and swift guanxi as an initial relationship state and an enhanced relationship state, respectively. Results will contribute toward IS literature by improving our understanding of social interaction and its effect on consumers’ perceptions and behaviors in a live-streaming shopping website. Furthermore, such findings can be leveraged to promote live-streaming technology among retailers planning to stimulate consumers’ purchase behavior