Research Directions, Challenges and Issues in Opinion Mining

Rapid growth of Internet and availability of user reviews on the web for any product has provided a need for an effective system to analyze the web reviews. Such reviews are useful to some extent, promising both the customers and product manufacturers. For any popular product, the number of reviews can be in hundreds or even thousands. This creates difficulty for a customer to analyze them and make important decisions on whether to purchase the product or to not. Mining such product reviews or opinions is termed as opinion mining which is broadly classified into two main categories namely facts and opinions. Though there are several approaches for opinion mining, there remains a challenge to decide on the recommendation provided by the system. In this paper, we analyze the basics of opinion mining, challenges, pros & cons of past opinion mining systems and provide some directions for the future research work, focusing on the challenges and issues

Sentiment Analysis Of Web Forums: Comparison Between SentiWordNet And SentiStrength

Internet has become a major tool for communication, training, fundraising, media operations, and recruitment, and these processes often use web forums. This paper intended to find suitable technique for analysing selected web forums that included radical content by presenting a comparison between SentiWordNet and SentiStrength. SentiWordNet is a lexical resource for supporting opinion mining by assigning a positivity score and a negativity score to each WordNet. SentiStrength is a technique that was developed from comments on MySpace. It uses human-designed lexical and emotional terms with a set of amplification, diminishing and negation rules. The results have been presented and discussed

Affect Analysis of Radical Contents on Web Forums Using SentiWordNet

The internet has become a major tool for communication, training, fundraising, media operations, and recruitment, and these processes often use web forums. This paper presents a model that was built using SentiWordNet, WordNet and NLTK to analyze selected web forums that included radical content. SentiWordNet is a lexical resource for supporting opinion mining by assigning a positivity score and a negativity score to each WordNet. The approaches of the model measure and identify sentiment polarity and affect the intensity of that which appears in the web forum. The results show that SentiWordNet can be used for analyzing sentences that appear in web forums

Social media research: influencing the influencers

One of the central concepts in marketing theory is the idea that some individuals are more influential than others, and that these influencers play a central role in driving adoption of new products and services. From a customer service perspective, when these influencers are dissatisfied, they are able to drive disproportionally large numbers of customers, and potential customers, away. This report includes two pieces of research to help organisations engage with, and manage, online influencers. The first investigates the role of hyperinfluencers in online rate-and-review sites. Whilst existing research suggests that most individuals who post online are motivated by feelings of altruism or reciprocity this study found that the hyperinfluencers viewed reviewing products as a form of entertainment, creating ‘game’ elements out of the review process. The second piece of research examined the role of influence on social media sites, specifically Facebook, and questions whether it is possible to build effective brand communities on Facebook. The effectiveness of Facebook as a tool for building relationships with customers has been questioned, with some arguing that Facebook has only a limited value for marketers as a platform for promotions and offers. The research indicates that effective brand communities can be built on Facebook, but many brands are currently adopting social media community strategies that actually destroy brand value. For both pieces of research recommendations are provided for best practice in maximising the beneficial effect of online influencers, and minimising the potential for damaging brands online

Optical tomography: Image improvement using mixed projection of parallel and fan beam modes

Mixed parallel and fan beam projection is a technique used to increase the quality images. This research focuses on enhancing the image quality in optical tomography. Image quality can be defined by measuring the Peak Signal to Noise Ratio (PSNR) and Normalized Mean Square Error (NMSE) parameters. The findings of this research prove that by combining parallel and fan beam projection, the image quality can be increased by more than 10%in terms of its PSNR value and more than 100% in terms of its NMSE value compared to a single parallel beam

Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline

Profiles of social networking sites users in the Netherlands

Online social networking has become a reality and integral part of the daily personal, social and business life. The extraordinary increase of the user numbers of Social Networking Sites (SNS) and the rampant creation of online communities presents businesses with many challenges and opportunities. From the commercial perspective, the SNS are an interesting and promising field: online social networks are important sources of market intelligence and also offer interesting options for co-operation, networking and marketing. For SMEs especially the Social Networking Sites represent a simple and low cost solution for listening the customer’s voice, reaching potential customers and creating extensive business networks. This paper presents the results of a national survey mapping the demographic, social and behavioral characteristics of the Dutch users of SNS. The study identifies four different user profiles and proposes a segmentation framework as basis for better understanding the nature and behavior of the participants in online communities. The findings present new insights to marketing strategists eager to use the communication potential of such communities; the findings are also interesting for businesses willing to explore the potential of online networking as a low cost yet very efficient alternative to physical, traditional networking

Word of Mouth, the Importance of Reviews and Ratings in Tourism Marketing

The Internet and social media have given place to what is commonly known as the democratization of content and this phenomenon is changing the way that consumers and companies interact. Business strategies are shifting from influencing consumers directly and induce sales to mediating the influence that Internet users have on each other. A consumer review is “a mixture of fact and opinion, impression and sentiment, found and unfound tidbits, experiences, and even rumor” (Blackshaw & Nazarro, 2006). Consumers' comments are seen as honest and transparent, but it is their subjective perception what shapes the behavior of other potential consumers. With the emergence of the Internet, tourists search for information and reviews of destinations, hotels or services. Several studies have highlighted the great influence of online reputation through reviews and ratings and how it affects purchasing decisions by others (Schuckert, Liu, & Law, 2015). These reviews are seen as unbiased and trustworthy, and considered to reduce uncertainty and perceived risks (Gretzel & Yoo, 2008; Park & Nicolau, 2015). Before choosing a destination, tourists are likely to spend a significant amount of time searching for information including reviews of other tourists posted on the Internet. The average traveler browses 38 websites prior to purchasing vacation packages (Schaal, 2013), which may include tourism forums, online reviews in booking sites and other generic social media websites such as Facebook and Twitter.Peer reviewedFinal Accepted Versio