one of the most important issues related to knowledge discovery is the field of comment mining. opinion mining is a tool through which the opinions of people who comment about a specific issue can be evaluated in order to achieve some interesting results. this is a subset of data mining. opinion mining can be improved using the data mining algorithms. one of the important parts of opinion minin...

Text mining is one of Artificial Intelligent (AI) technologies that uses Natural Language Processing (NLP) for extracting data from structured text. Sentiment analysis (also known as opinion mining) text techniques, which the computational study personals' behaviours and opinions. The importance sentiment increases extensively with enormous growth internet sites such e-commerce, blogs, social m...

Opinion Mining also known as Sentiment Analysis (SA) has recently become the focus of many researchers, because analysis online text is useful and demanded in different applications. social sentiments a trending topic this era users share their emotions more suitable format with help micro blogging services like twitter. Twitter provides information about individual's real-time feelings through...

Recent considerations in opinion mining, oriented by real applicative tasks, require creating lexical and semantic resources quantitatively and qualitatively rich. In this context, we present a method to automatically enhance a lexicon of subjective terms. The method relies on the indexing of Web documents by a search engine and large number of requests automatically sent. The construction of t...

The internet offers a powerful medium for expressing opinions, emotions and ideas, using online platforms supported by smartphone usage high penetration. Most posts are textual based can include people’s emotional feelings particular moment or sentiment. Monitoring sentiments opinions is important detecting any excessive triggered citizens which lead to unintended consequences threats national ...

Lexicon-based classifier is in the long term one of the main and most effective methods of polarity classification used in sentiment analysis, i.e. computational study of opinions, sentiments and emotions expressed in text (see Liu, 2010). Although it achieves relatively good results also for Czech, the classifier still shows some error rate. This paper provides a detailed analysis of such erro...

This paper introduces a novel deep learning framework including a lexicon-based approach for sentencelevel prediction of sentiment label distribution. We propose to first apply semantic rules and then use a Deep Convolutional Neural Network (DeepCNN) for character-level embeddings in order to increase information for word-level embedding. After that, a Bidirectional Long Short-Term Memory netwo...

Sentiment analysis or opinion mining involves systamtically extracting, identifying and quantifying subjective information using text natural language processing algorithms. The paper explores the recent research work in field of sentiment categorizes into five unique domains. This proposes a three stage framework involving data gathering, preparation phases. proposed is applied to tweets on Ru...

This paper describes an annotation scheme for argumentation in opinionated texts such as newspaper editorials, developed from a corpus of approximately 500 English texts from Nepali and international newspaper sources. We present the results of analysis and evaluation of the corpus annotation – currently, the inter-annotator agreement kappa value being 0.80 which indicates substantial agreement...

This review paper presents a comprehensive analysis of 10 selected research papers that investigate the interplay between social media, gamification, and sentiment analysis. The cover wide range topics, including customer engagement, user behaviour in mobile apps, sustainable change, opinion mining, techniques, applications on media data. offers valuable insights into effects gamification engag...