Sentiment analysis algorithms and applications: A survey

Abstract

Sentiment analysis is a field of study for analyzing people's emotions, such as Nice, Happy, ਦੁ ਖੀ (sad), changa (Good), etc. towards the entities and attributes expressed in written text. It noticed that, on microblogging websites (Facebook, YouTube, Twitter ), most people used more than one language to express their emotions. The change of one language to another language within the same written text is called code-mixing.In this research, we gathered the English-Punjabi code-mixed corpus from micro-blogging websites. We have performed language identification of code-mix text, which includes Phonetic Typing, Abbreviation, Wordplay, Intentionally misspelled words and Slang words. Then we performed tokenization of English and Punjabi language words consisting of different spellings. Then we performed sentiment analysis based on the above text based on the lexicon approach. The dictionary created for English Punjabi code mixed consists of opinionated words. The opinionated words are then categorized into three categories i.e. positive words list, negative words list, and neutral words list. The rest of the words are being stored in an unsorted word list. By using the Ngram approach, a statistical technique is applied at sentence level sentiment polarity of the English-Punjabi codemixed dataset. Our results show an accuracy of 83% with an F-1 measure of 77%.

Statistical Technology Analysis for Competitive Sustainability of Three Dimensional Printing

“…If we can combine the results of this paper with expert opinions, we can expect a more accurate and valid result for sustainable technology analysis between competitors. Thus, in our future work, we will apply opinion mining [56], sentiment analysis [57], and topic model [58,59] to our methodology for sustainable technology analysis. This paper dealt with a more efficient way of finding sustainability in a specific technology field by introducing a new time concept that was not covered in the existing quantitative analysis methods for selecting sustainable technologies.…”

Aplicando Redes Neurais sem Peso em Mineração de Opinião no Twitter

“…De uma forma geral, o modelo bag-of-wordś e uma representação muito simples, ondeé ignorada a ordem das palavras nos documentos, limitando-se a contar o número de ocorrências de cada palavra (feature) [11]. Outro fator relevante quantoà escolha dos algoritmosé o fato de serem amplamente utilizados em diversos trabalhos no mesmo tema [12].…”

Lexicon Based Sentiment Analysis of Twitter Data

“…Pang and Lee [15] in their review covers techniques and approaches and challenges of Sentiment Analysis. Liu [16] in his book provides an in depth introduction to Sentiment Analysis and presents a comprehensive survey of all important research topics and the latest developments in the field. Medhat et al [17] have done a meta analysis of 54 published articles to illustrate trend in research of the sentiment analysis applications and algorithms.…”