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Implications of Perceived Utility on Individual Choice and Preferences: A New Framework for Designing Recommender System
Consumer psychology and consumer behaviour has constantly been a field of interest for the researchers. Volumes of researches are available in this area, still new theories and concepts keep emerging in response to change in context and environment. Consumer psychology has large cross disciplinary implications. In this paper, a relationship between consumer psychology and recommender system has been explained and how implementing a consumer psychology model can improve recommender system performance. This paper also gives first level analysis of various filters that can be developed along with the design of recommender system in order to generate a more refined and relevant choice sets. There are attraction effects observed among different items and the attractiveness of a product is co- dependent on attractiveness of other options available in a choice set. In the present paper, we have explored the utility of defender model in the design of recommender systems. Different effects like decoy and asymmetric dominance are als
Personality Identification from Social Media Using Deep Learning: A Review
Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed