Data Mining - Concepts and Techniques.

How to Do Things With Words

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online.

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Sentiment Analysis and Opinion Mining

A systematic search of the research literature from 1996 through July 2008 identified more than a thousand empirical studies of online learning. Analysts screened these studies to find those that (a) contrasted an online to a face-to-face condition, (b) measured student learning outcomes, (c) used a rigorous research design, and (d) provided adequate information to calculate an effect size. As a result of this screening, 51 independent effects were identified that could be subjected to meta-analysis. The meta-analysis found that, on average, students in online learning conditions performed better than those receiving face-to-face instruction. The difference between student outcomes for online and face-to-face classes—measured as the difference between treatment and control means, divided by the pooled standard deviation—was larger in those studies contrasting conditions that blended elements of online and face-to-face instruction with conditions taught entirely face-to-face. Analysts noted that these blended conditions often included additional learning time and instructional elements not received by students in control conditions. This finding suggests that the positive effects associated with blended learning should not be attributed to the media, per se. An unexpected finding was the small number of rigorous published studies contrasting online and face-to-face learning conditions for K–12 students. In light of this small corpus, caution is required in generalizing to the K–12 population because the results are derived for the most part from studies in other settings (e.g., medical training, higher education).

Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies

Individualism and collectivism

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Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness

In an e-learning environment that emphasizes learner-centered activity and system interactivity, remote learners can outperform traditional classroom students.

Can e-learning replace classroom learning?

Since the late 1990s, online shopping has taken off as an increasing number of consumers purchase increasingly diversified products on the Internet. Given that how to attract and retain consumers is critical to the success of online retailers, research on the antecedents of consumer acceptance of online shopping has attracted widespread attention. There has yet to be a holistic view of online shopping acceptance from the perspective of consumers. In this research, we conducted an extensive survey of extant related studies and synthesized their findings into a reference model called OSAM (Online Shopping Acceptance Model) to explain consumer acceptance of online shopping. Our literature survey reveals that a myriad of factors have been examined in the context of online shopping and mixed results on those factors have been reported. The proposed model helps reconcile conflicting findings, discover recent trends in this line of research, and shed light on future research directions.

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Online shopping acceptance model — a critical survey of consumer factors in online shopping

Usability testing of software applications developed for mobile devices is an emerging research area that faces a variety of challenges due to unique features of mobile devices, limited bandwidth, unreliability of wireless networks, as well as changing context (environmental factors) Traditional guidelines and methods used in usability testing of desktop applications may not be directly applicable to a mobile environment Therefore, it is essential to develop and adopt appropriate research methodologies that can evaluate the usability of mobile applications The contribution of this article is to propose a generic framework for conducting usability tests for mobile applications through discussing research questions, methodologies, and usability attributes The article provides an overview of existing mobil application usability studies and discusses major research questions that have been investigated Then, it proposes a generic framework and provides detailed guidelines on how to conduct such usability

Challenges, Methodologies, and Issues in the Usability Testing of Mobile Applications

Despite the publicity regarding big data and analytics (BDA), the success rate of these projects and strategic value created from them are unclear. Most literature on BDA focuses on how it can be u...

Dongsong Zhang

Papers

Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness

Can e-learning replace classroom learning?

Online shopping acceptance model — a critical survey of consumer factors in online shopping

Challenges, Methodologies, and Issues in the Usability Testing of Mobile Applications

Creating Strategic Business Value from Big Data Analytics: A Research Framework