Consumers’ purchase decisions are increasingly influenced by user-generated online reviews. Accordingly, there has been growing concern about the potential for posting deceptive opinion spam— fictitious reviews that have been deliberately written to sound authentic, to deceive the reader. In this paper, we explore generalized approaches for identifying online deceptive opinion spam based on a n...

This research attempts to understand user adoption of fashionable technologies (e.g., iPhone or iPad) and the influence of fashion waves on adopters of both fashionable and non-fashionable technologies. A research model was developed based on the regret theory. We tested the model by examining 20,122 customer reviews collected from Amazon.com. A theory-driven naïve Bayes classifier was develope...

Internet has increasingly become the place for online learning, and exchange of ideas. The rapid development in wireless technology offering fast data transfer has lead to mobile device revolution. With the ease of access of mobile devices like mobile phones, PDAs, tablet PCs and high bandwidth through wireless, there is an upsurge of mobile learning or Mlearning. It is important to know the op...

Nadheesh Jihan, Yasas Senarath, Dulanjaya Tennekoon, Mithila Wickramarathne, and Surangika Ranathunga Department of Computer Science and Engineering, University of Moratuwa, Katubedda 10400, Sri Lanka {nadheeshj.13, wayasas.13, dulanjayatennekoon.13, mithwick.13, surangika}@cse.mrt.ac.lk Abstract This paper describes a system to extract aspect categories for the task of aspect based sentiment a...

We design an algorithm to solve the following problem. Given a document, we classify the sentiment of the document as either positive or negative. This problem is known as binary sentiment analysis and has broad applications. For example, it can be used to understand the customer feedback for a particular product automatically without manually reading all the reviews. In this particular assignm...