Related papers: Predictive Analysis on Twitter: Techniques and App…

Linguistics has been instrumental in developing a deeper understanding of human nature. Words are indispensable to bequeath the thoughts, emotions, and purpose of any human interaction, and critically analyzing these words can elucidate the…

We show that information about social relationships can be used to improve user-level sentiment analysis. The main motivation behind our approach is that users that are somehow "connected" may be more likely to hold similar opinions;…

Microblogs such as Twitter represent a powerful source of information. Part of this information can be aggregated beyond the level of individual posts. Some of this aggregated information is referring to events that could or should be acted…

Sentiment analysis of online user generated content is important for many social media analytics tasks. Researchers have largely relied on textual sentiment analysis to develop systems to predict political elections, measure economic…

Inferring socioeconomic attributes of social media users such as occupation and income is an important problem in computational social science. Automated inference of such characteristics has applications in personalised recommender…

Twitter has become a major source of data for social media researchers. One important aspect of Twitter not previously considered are {\em deletions} -- removal of tweets from the stream. Deletions can be due to a multitude of reasons such…

Millions of people express themselves on public social media, such as Twitter. Through their posts, these people may reveal themselves as potentially valuable sources of information. For example, real-time information about an event might…

Recent studies on domain-specific BERT models show that effectiveness on downstream tasks can be improved when models are pretrained on in-domain data. Often, the pretraining data used in these models are selected based on their subject…

This paper studies the relation between activity on Twitter and sales. While research exists into the relation between Tweets and movie and book sales, this paper shows that the same relations do not hold for products that receive less…

Twitter is increasingly used for political, advertising and marketing campaigns, where the main aim is to influence users to support specific causes, individuals or groups. We propose a novel methodology for mining and analyzing Twitter…

With the rise of social media as an important channel for the debate and discussion of public affairs, online social networks such as Twitter have become important platforms for public information and engagement by policy makers. To…

The social media network phenomenon leads to a massive amount of valuable data that is available online and easy to access. Many users share images, videos, comments, reviews, news and opinions on different social networks sites, with…

Social media data has been increasingly used to study biomedical and health-related phenomena. From cohort level discussions of a condition to planetary level analyses of sentiment, social media has provided scientists with unprecedented…

Data Stream Mining is one of the area gaining lot of practical significance and is progressing at a brisk pace with new methods, methodologies and findings in various applications related to medicine, computer science, bioinformatics and…

Data extracted from social media platforms, such as Twitter, are both large in scale and complex in nature, since they contain both unstructured text, as well as structured data, such as time stamps and interactions between users. A key…

Automatic profiling of social media users is an important task for supporting a multitude of downstream applications. While a number of studies have used social media content to extract and study collective social attributes, there is a…

In this paper , we tackle Sentiment Analysis conditioned on a Topic in Twitter data using Deep Learning . We propose a 2-tier approach : In the first phase we create our own Word Embeddings and see that they do perform better than…

As humans, we can often detect from a persons utterances if he or she is in favor of or against a given target entity (topic, product, another person, etc). But from the perspective of a computer, we need means to automatically deduce the…

Sentiment Analysis is a vital research topic in the field of Computer Science. With the accelerated development of Information Technology and social networks, a massive amount of data related to comment texts has been generated on web…

Nowadays, internet has changed the world into a global village. Social Media has reduced the gaps among the individuals. Previously communication was a time consuming and expensive task between the people. Social Media has earned fame…