People use microblogging platforms like Twitter to involve with other users for a wide range of interests and practices. Twitter profiles run by different types of users such as humans, bots, spammers, businesses, professionals. This research work identifies six broad classes of Twitter users, and employs a supervised machine learning approach which uses a comprehensive set of features to class...

Although the social medium Twitter grants users freedom of speech, its instantaneous nature and retweeting features also amplify hate speech. Because Twitter has a sizeable black constituency, racist tweets against blacks are especially detrimental in the Twitter community, though this effect may not be obvious against a backdrop of half a billion tweets a day. We apply a supervised machine lea...

INTRODUCTION Twitter channels are increasingly popular at medical conferences. Many groups, including healthcare providers and third party entities (e.g., pharmaceutical or medical device companies) use these channels to communicate with one another. These channels are unregulated and can allow third party commercial entities to exert an equal or greater amount of Twitter influence than healthc...

Twitter is one of the most visited sites in these days. Twitter spam, however, is constantly increasing. Since Twitter spam is different from traditional spam such as email and blog spam, conventional spam filtering methods are inappropriate to detect it. Thus, many researchers have proposed schemes to detect spammers in Twitter. These schemes are based on the features of spam accounts such as ...

T witter has become one of the most commonly used communication tools in daily life. With 500 million users, Twitter now generates more than 500 million tweets per day. However, its popularity has also attracted spamming. Spammers spread many intensive tweets, which can lure legitimate users to commercial or malicious sites containing malware downloads, phishing, drug sales, scams, and more.1 S...

We observe many CEOs of big companies as easily as movie stars or sports players on Twitter. Why do they appear on social media and what would be the effect of their Twitter network on the corporate performance and shareholder benefit? This study explores big company CEOs on Twitter. We identify Twitterusing CEOs and examine the impact of their social media activity on the corporate performance...

This paper is part of a wider work studying the co-influences of Twitter and the production of information by traditional media. A strong prerequisite of this study is to collect, with the limitations of the Twitter API, tweets linked to media events that are representative of the real Twitter activity. This paper describes two proposed approaches to handle this important task. The first one, i...

Data mining of Social networks is a new but interesting field within Data Mining. We leverage the power of sentiment analysis to detect bullying instances in Twitter. We are interested in understanding bullying in social networks, especially in Twitter. To best of our understanding, there is no previous work on using sentiment analysis to detect bullying instances. Our training data set consist...

Microbloging is an extremely prevalent broadcast medium amidst the Internet fraternity these days. People share their opinions and sentiments about variety of subjects like products, news, institutions, etc., every day on microbloging websites. Sentiment analysis plays a key role in prediction systems, opinion mining systems, etc. Twitter, one of the microbloging platforms allows a limit of 140...