Search Results

A deep learning-based Hybrid Fine Tuned Smith Algorithm with Adam optimiser (HFS-AO) is introduced for multilingual opinion mining. Initially, data are collected using the web scraping algorithm to collect three different languages data: Marathi, Hindi ...

The peer review process is the main academic resource to ensure that science advances and is disseminated. To contribute to this important process, classification models capable of predicting the score of a review text (RSP) and the final decision of a ...

The rise of digital communication systems provides an almost infinite source of information that can be useful to feed classification algorithms, so it makes use of an already categorized collection of opinions of the social network Twitter for the ...

A thorough analysis of people’s sentiment about a business, an event or an individual is necessary for business development, event analysis and popularity assessment. Social networks are rich sources of obtaining user opinions about people, events and ...

In this paper, we propose a novel approach for text classification based on clustering word embeddings, inspired by the bag of visual words model, which is widely used in computer vision. After each word in a collection of documents is represented as ...

String kernels have successfully been used for various NLP tasks, ranging from text categorization by topic to native language identification. In this paper, we present a simple and efficient algorithm for computing various spectrum string kernels. When ...

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 opinion mining, but it should also encompass emotion mining. Opinion ...

The fact that people freely express their opinions and ideas in no more than 140 characters makes Twitter one of the most prevalent social networking websites in the world. Being popular in Saudi Arabia, we believe that tweets are a good source to ...

Every day more companies are interested in users' opinions about their products or services. Also, every day there are more users that search for reviews on the web before purchasing a product. These users and companies are not satisfied with knowing ...

It was not until 2010 when businesses, politicians and people in general began to realize the potential of Twitter in Spain. This fact has awoken research interest in the extraction of knowledge from Twitter. This paper aims to fill the gap of the lack ...

With people increasingly using emoticons in written text on the Web in order to express, stress, or disambiguate their sentiment, it is crucial for automated sentiment analysis tools to correctly account for such graphical cues for sentiment. We analyze ...

With the rapid growth of data generated by social web applications new paradigms in the generation of knowledge are opening. This paper introduces Crowd Explicit Sentiment Analysis (CESA) as an approach for sentiment analysis in social media ...

Sentiment analysis has drawn considerable interest among researchers owing to the realization of its fascinating commercial and business benefits. This paper deals with sentiment analysis in Arabic text from three perspectives. First, several ...

Sentiment analysis is an area of research that has gained considerable attention in recent years due to the increasing availability of opinionated information online. The majority of the work in sentiment analysis considers the polarity of word terms ...

This work presents a novel method for the generation of a knowledge base oriented to Sentiment Analysis from the continuous stream of published micro-blogs in social media services like Twitter. The method is simple in its approach and has shown to be ...

Sentiment analysis has gained a lot of attention in recent years, mainly due to the many practical applications it supports and a growing demand for such applications. This growing demand is supported by an increasing amount and availability of ...

For sentiment classification, there exist a heterogeneous mass of resources such as semantic dictionaries, unlabeled corpora, and heuristic rules. In this paper, based on a graph-based semi-supervised algorithm, we focus on exploiting multiple resources ...

The idea of applying a conjunction of sentiment and social network analysis to improve the performance of applications has recently attracted attention of researchers. In widely used online shopping websites, customers can provide reviews about a ...

Sentiment Analysis over Social Media facilitates the extraction of useful conclusions about the average public opinion on a variety of topics, but poses serious technical challenges. This is because of the sparse, noisy, multilingual content that is ...

Recent sentiment analysis research has focused on the functional relations of words using typed dependency parsing as this provides a refined analysis on the grammar and semantics of the textual data, which could improve performance. However, typed ...