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Even though the Internet and social media have increased the amount of news and information people can consume, most users are only exposed to content that reinforces their positions and isolates them from other ideological communities.…

Rapid increase in the volume of sentiment rich social media on the web has resulted in an increased interest among researchers regarding Sentimental Analysis and opinion mining. However, with so much social media available on the web,…

In todays competitive business world, being aware of customer needs and market-oriented production is a key success factor for industries. To this aim, the use of efficient analytic algorithms ensures a better understanding of customer…

Keeping up to date on emerging entities that appear every day is indispensable for various applications, such as social-trend analysis and marketing research. Previous studies have attempted to detect unseen entities that are not registered…

While social networks can provide an ideal platform for up-to-date information from individuals across the world, it has also proved to be a place where rumours fester and accidental or deliberate misinformation often emerges. In this…

Microblog, an online-based broadcast medium, is a widely used forum for people to share their thoughts and opinions. Recently, Emotion Recognition (ER) from microblogs is an inspiring research topic in diverse areas. In the machine learning…

Since the length of microblog texts, such as tweets, is strictly limited to 140 characters, traditional Information Retrieval techniques suffer from the vocabulary mismatch problem severely and cannot yield good performance in the context…

Rapid increase in internet users along with growing power of online review sites and social media has given birth to sentiment analysis or opinion mining, which aims at determining what other people think and comment. Sentiments or Opinions…

Social media is a rich source of user behavior and opinions. Twitter senses nearly 500 million tweets per day from 328 million users.An appropriate machine learning pipeline over this information enables up-to-date and cost-effective data…

Online social microblogging platforms including Twitter are increasingly used for aiding relief operations during disaster events. During most of the calamities that can be natural disasters or even armed attacks, non-governmental…

In this paper we present a method to identify tweets that a user may find interesting enough to retweet. The method is based on a global, but personalized classifier, which is trained on data from several users, represented in terms of…

Recommendation systems are important intelligent systems that play a vital role in providing selective information to users. Traditional approaches in recommendation systems include collaborative filtering and content-based filtering.…

Predictive analysis of social media data has attracted considerable attention from the research community as well as the business world because of the essential and actionable information it can provide. Over the years, extensive…

What tweet features are associated with higher effectiveness in tweets? Through the mining of 122 million engagements of 2.5 million original tweets, we present a systematic review of tweet time, entities, composition, and user account…

With the increasing abundance of 'digital footprints' left by human interactions in online environments, e.g., social media and app use, the ability to model complex human behavior has become increasingly possible. Many approaches have been…

Understanding latent user needs beneath shopping behaviors is critical to e-commercial applications. Without a proper definition of user needs in e-commerce, most industry solutions are not driven directly by user needs at current stage,…

Social media expose millions of users every day to information campaigns --- some emerging organically from grassroots activity, others sustained by advertising or other coordinated efforts. These campaigns contribute to the shaping of…

Social media offer plenty of information to perform market research in order to meet the requirements of customers. One way how this research is conducted is that a domain expert gathers and categorizes user-generated content into a complex…

This work proposes a novel framework for the development of new products and services in transportation through an open innovation approach based on automatic content analysis of social media data. The framework is able to extract users…

Traditional methods of collecting user feedback through transit surveys are often time-consuming, resource intensive, and costly. In this paper, we propose a novel NLP-based framework that harnesses the vast, abundant, and inexpensive data…