New Avenues in Opinion Mining and Sentiment Analysis

  title={New Avenues in Opinion Mining and Sentiment Analysis},
  author={E. Cambria and Bj{\"o}rn Schuller and Yunqing Xia and Catherine Havasi},
  journal={IEEE Intelligent Systems},
The Web holds valuable, vast, and unstructured information about public opinion. Here, the history, current use, and future of opinion mining and sentiment analysis are discussed, along with relevant techniques and tools. 

A Survey on Sentiment Analysis Algorithms and Techniques

  • S. J
  • Computer Science
  • 2020
Insight is given on SA algorithms and techniques used to gather and analyze text and classify it into positive, negative and neutral is explained using Natural language processing.

Searching for the Most Negative Opinions

No sentiment analysis approach has considered the automatic identification and extraction of the most negative opinions, in spite of their significant impact in many fields such as industry, trade, political and socials issues.

Opinion Mining: Applications Trends

This paper aimed to presents a literature review regarding sentiment analysis and opinion mining recent applications area.

A Sneak Preview of Sentiment Analysis

  • Roopal MamtoraL. Ragha
  • Computer Science
    2018 International Conference on Smart City and Emerging Technology (ICSCET)
  • 2018
This survey paper contributes towards complete information about emotions detected in various modalities, tasks, techniques, application domains and available built-in resources related to sentiment analysis.

Sentiment Analysis Using Ensemble Learners and Gini Index

The sentiment evaluation using gini index feature selection method and the ensemble learners method has been used for classification and the results have been obtained from the confusion matrix.

Sentiment analysis of tweets in comparison to a company’s financial performance

This study analyzes peoples reactions in social media to the release of a company’s quarterly report. Sentiment analysis was performed on tweets about a company both from a short-and long-term pers

Public Opinion Detection in an Online Lending Forum: Sentiment Analysis and Data Visualization

  • G. ZhanMing WangMeiyi Zhan
  • Computer Science
    2020 IEEE 5th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA)
  • 2020
This research aims to employ natural language processing (NLP), sentiment analysis and data mining technologies to build a public opinion analysis system to serve enterprises' need of online public opinion detection.

A Machine Learning Approach to Multi-Scale Sentiment Analysis of Amharic Online Posts

A multi-scale sentiment analysis model for Amharic using supervised machine learning is presented, which classifies opinions as positive and negative based on polarity of words.

Harvesting Opinions and Emotions from Social Media Textual Resources

Multiple approaches are considered, with an emphasis on detecting sentiments in Web 2.0 textual resources, for accurately capturing the conveyed sentiments in social media textual resources.

A lexicon based method to search for extreme opinions

This work uses an unsupervised approach to search for extreme opinions, which is based on the automatic construction of a new lexicon containing the most negative and most positive words.



39. Opinion mining and sentiment analysis

This chapter introduces an idealised, end-to-end opinion analysis system and describes its components, including constructing opinion lexica, performing sentiment analysis, and producing opinion summaries.

Twitter as a Corpus for Sentiment Analysis and Opinion Mining

This paper shows how to automatically collect a corpus for sentiment analysis and opinion mining purposes and builds a sentiment classifier, that is able to determine positive, negative and neutral sentiments for a document.

Sentiment Analysis and Opinion Mining

  • Lei ZhangB. Liu
  • Computer Science
    Encyclopedia of Machine Learning and Data Mining
  • 2012
This book is a comprehensive introductory and survey text that covers all important topics and the latest developments in the field with over 400 references and is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular.

Opinion mining of customer feedback data on the web

This paper surveys and analyzes various techniques that have been developed for the key tasks of opinion mining and provides an overall picture of what is involved in developing a software system for opinion mining.

Opinion Mining on Newspaper Quotations

A comparative study on the methods and resources that can be employed for mining opinions from quotations in newspaper articles concludes that a generic opinion mining system requires both the use of large lexicons, as well as specialised training and testing data.

Hidden sentiment association in chinese web opinion mining

A novel mutual reinforcement approach to deal with the feature-level opinion mining problem, which can largely predict opinions relating to different product features, even for the case without the explicit appearance of product feature words in reviews.

Generalizing Dependency Features for Opinion Mining

Using a transformation of dependency relation triples, features based on syntactic dependency relations can be utilized to improve performance on opinion mining by being converted into composite back-off features that generalize better than the regular lexicalized dependency relation features.

Preface to sentiment elicitation from natural text for information retrieval and extraction

Next-generation opinion mining systems should employ techniques capable to better grasp the conceptual rules that govern sentiment and the clues that can convey these concepts from realization to verbalization in the human mind.

Thumbs up? Sentiment Classification using Machine Learning Techniques

This work considers the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative, and concludes by examining factors that make the sentiment classification problem more challenging.

A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts

A novel machine-learning method is proposed that applies text-categorization techniques to just the subjective portions of the document, which greatly facilitates incorporation of cross-sentence contextual constraints.