Is That Twitter Hashtag Worth Reading

Online social media such as Twitter, Facebook, Wikis and Linkedin have made a great impact on the way we consume information in our day to day life. Now it has become increasingly important that we come across appropriate content from the social media to avoid information explosion. In case of Twitter, popular information can be tracked using hashtags. Studying the characteristics of tweets containing hashtags becomes important for a number of tasks, such as breaking news detection, personalized message recommendation, friends recommendation, and sentiment analysis among others. In this paper, we have analyzed Twitter data based on trending hashtags, which is widely used nowadays. We have used event based hashtags to know users' thoughts on those events and to decide whether the rest of the users might find it interesting or not. We have used topic modeling, which reveals the hidden thematic structure of the documents (tweets in this case) in addition to sentiment analysis in exploring and summarizing the content of the documents. A technique to find the interestingness of event based twitter hashtag and the associated sentiment has been proposed. The proposed technique helps twitter follower to read, relevant and interesting hashtag.Comment: 10 pages, 6 figures, Presented at the Third International Symposium on Women in Computing and Informatics (WCI-2015

Investigating Predictive Power of Stock Micro Blog Sentiment in Forecasting Future Stock Price Directional Movement

This study attempts to discover and evaluate the predictive power of stock micro blog sentiment on future stock price directional movements. We construct a set of robust models based on sentiment analysis and data mining algorithms. Using 72,221 micro blog postings for 1909 stock tickers and 3874 distinct authors, our study reveals not only that stock micro blog sentiments do have predictive power for simple and market-adjusted returns respectively, but also that this predictive accuracy is consistent with the underreaction hypothesis observed in behavioral finance. We establish that stock micro blog with its succinctness, high volume and real-time features do have predictive power over future stock price movements. Furthermore, this study provides support for the model of irrational investor sentiment, recommends a supplementary investing approach using user-generated content and validates an instrument that may contribute to the monetization schemes for Virtual Investing Communities

Emergence of Things Felt: Harnessing the Semantic Space of Facebook Feeling Tags

In 2013 Facebook launched a feature allowing users to add a feeling tag to their posts. We have collected 18 months worth of such public posts. Our aim is to map the semantic space of ‘Facebook feelings’ to understand patterns in how feelings are tagged and how they can be described in terms of valence and arousal. Our findings reveal temporal and social patterns in the most commonly shared feelings. In line with the ‘exhibitional’ nature of Facebook, our analyses indicate that ‘extreme’ feelings, such as excitement and anger, may be expressed in even more extreme levels of both valence and arousal. Facebook also provides novel emotional scripts (e.g., “meh”) that help people express feelings in ways that traditionally socialized feelings do not. This understanding of the semantic space of ‘Facebook feelings’ ultimately serves to inform the development of an automatic ‘Feelings Meter’

Effectiveness of Corporate Social Media Activities to Increase Relational Outcomes

This study applies social media analytics to investigate the impact of different corporate social media activities on user word of mouth and attitudinal loyalty. We conduct a multilevel analysis of approximately 5 million tweets regarding the main Twitter accounts of 28 large global companies. We empirically identify different social media activities in terms of social media management strategies (using social media management tools or the web-frontend client), account types (broadcasting or receiving information), and communicative approaches (conversational or disseminative). We find positive effects of social media management tools, broadcasting accounts, and conversational communication on public perception

Sentiment analysis on Chinese web forums using elastic nets: Features, classification and interpretation: Working paper series--11-11

Consumer opinion has always been of great concern for businesses and others in the commercial sector. Among all social media which contain opinion-rich content, Web forums have become influential due to the large volume of discussions and high levels of interactivity. The Chinese market has now emerged as one of the largest ones over the world, therefore understanding the opinions and sentiments expressed by Chinese consumers has become increasingly important. In this study, we proposed a generic framework to analyze sentiment in Chinese Web forums. To detect online sentiment, we developed a classification method using Elastic Nets with rich feature representation. The proposed sentiment analysis framework was evaluated on two of the most famous Chinese forums with topics on Chinese stock market and laptop. Findings about interesting features were discussed

When Madison Avenue turns into Main Street: Consumer generated advertising as a marketing tool and its effects on online word of mouth

The purpose of this study is to investigate the effectiveness of consumer generated advertising as a marketing tool to encourage online word of mouth. Subsequently, the researchers aim to examine if there are certain design factors in consumer generated advertising that influence the effectiveness of consumer generated advertising in encouraging online word of mouth. The study conducts a multiple case study of several consumer generated advertising campaigns. It consists of in-depth studies of these cases in combination with quantitative analyses of the encouraged word of mouth. The different cases are examined on several design factors that could possible increase the volume of encouraged word of mouth