Top Research Papers on Sentiment Analysis

Sentiment analysis or opinion mining is the computational study of people’s opinions, appraisals, and emotions toward entities, events and their attributes in order to gather consumer opinions about its products and those of its competitors.

A common sentiment analysis task, the classification of IMDb (Internet Movie Database) movie reviews, is used to illustrate the methods on a common task that appears frequently in the literature.

This study illustrates how sentiment analysis can be utilised to obtain insights on the experiences of informal L2 learners when they engage with chatbots for L2 learning and suggests informal L1 learners have mixed sentiments on their experiences.

The field of sentiment analysis and opinion mining was introduced and the current state of the art was surveyed and the widely studied topic sentiment analysis based on Twitter and need of opinion spam detection was discussed.

This paper will analyze various classifiers that can be used to detection text based emotions during the Chennai floods and build a prototype to analyses this.

The majority of Indian inhabitants accept the Indian government's decision to enforce a lockdown during the corona outburst, according to the results of this survey.

This project is an exploration into sentiment analysis, aiming to construct a resilient sentiment analyzer through natural language processing (NLP), highlighting the need for ongoing training on evolving datasets and the integration of advanced NLP models to elevate accuracy levels.

One of the trendiest study fields in computer science nowadays is sentiment analysis (also known as emotional computing), and major statistical programs such as sas and spss contain sentiment analysis modules as standard features.

Today, tourism and hospitality consumers are not isolated anymore when making purchase decisions. Social media represent support networks that allow these consumers to tap into a vast universe of peer opinions, critiques, feedback, recommendations or warnings about specific tourism and hospitality products or services (Benckendorff et al., 2014; Hvass & Munar, 2012; Miguens et al., 2008; Milano et al., 2011; Munar & Jacobsen, 2014; Sigala et al., 2012; Thevenot, 2007; Xiang & Gretzel, 2010; Zeng & Gerritsen, 2014). This subjective and experience-based information can be expressed and published...

This paper will study about Sentiment analysis, steps to be followed in the sentiment analysis and its’ levels.

Review of the sentiment analysis concepts, methods and mechanisms for solving the issues discussed with different aspects, especially, pre-processing, mathematical and statistical mechanism are used in lexicon based approach for refereed papers, which was handled in sentiment analysis.

Different approaches to analyze persons’ opinions and challenges that emerge in this field of sentiment analysis are presented.

This paper describes the study of different sentiment analysis methods on different web resources such as review sites, blogs, discussion forums and news and gives overview of tools and application area of sentiment analysis.

A broad way of analyzing the methods and making conclusion provided by these methods of sentiment classification is provided, which aims to determine the attitude of a speaker or writer with respect to some topic of a document.

This survey would cover various approaches and methodology used in Sentiment Analysis and Opinion Mining in general, with a focus on Internet text like, Product review, tweets and other social media.

There are challenges in developing accurate sentiment analysis models for all languages, but there are applications in understanding public perception of eco-friendly transformation and air quality, predicting box office success, and analyzing public sentiment during global events such as pandemics.

This chapter studies recent advances in machine learning (ML) used for SMC analysis and its applications, and reports that ML has a significant contribution to SMC mining.

A Sentiment Analysis study performed on over than 1000 Facebook posts about newscasts is described, comparing the sentiment for Rai - the Italian public broadcasting service - towards the emerging and more dynamic private company La7.

Collecting a selected set of opinions and sentiments and then topic-oriented analysis allows extraction of rich information that would help make smarter business decisions, political campaigns and better product consumption.

インターネットが普及し, 一般の個人が手軽に情報発信できる環境が整ってきている. この個人の発信する情報には, ある対象に関するその人の評価等, 個人の意見が多く記述される.これらの評価情報を抽出し, 整理し, 提示することは, 対象の提供者である企業や, 対象を利用する立場の一般の人々双方にとって利点となる.このため, 自然言語処理の分野では, 近年急速に評価情報を扱う研究が活発化している.本論文では, このような現状の中, テキストから評価情報を発見, 抽出および整理, 集約する技術について, その基盤となる研究から最近の研究までを概説する.