Topic modeling is used in information retrieval to infer the hidden themes in a collection of
documents and thus provides an automatic means to organize, understand and summarize …

Sentiments or opinions from social media provide the most up-to-date and inclusive
information, due to the proliferation of social media and the low barrier for posting the …

Aspect-based sentiment analysis (ABSA), which aims to identify fine-grained opinion polarity
towards a specific aspect, is a challenging subtask of sentiment analysis (SA). In this paper …

Topic modeling is one of the most powerful techniques in text mining for data mining, latent
data discovery, and finding relationships among data and text documents. Researchers …

Sentiment analysis from text consists of extracting information about opinions, sentiments,
and even emotions conveyed by writers towards topics of interest. It is often equated to …

With the advent of Web 2.0, people became more eager to express and share their opinions
on web regarding day-to-day activities and global issues as well. Evolution of social media …

With the increasing development of Web 2.0, such as social media and online businesses,
the need for perception of opinions, attitudes, and emotions grows rapidly. Sentiment …

The field of sentiment analysis, in which sentiment is gathered, analyzed, and aggregated
from text, has seen a lot of attention in the last few years. The corresponding growth of the …

The goal of this research is to build a model to predict stock price movement using the
sentiment from social media. Unlike previous approaches where the overall moods or …

How can a single person understand what's going on in a collection of millions of
documents? This is an increasingly common problem: sifting through an organization's e …