A non-parametric LDA-based induction method for sentiment analysis

2012 ◽  
Author(s):  
Mohammadreza Shams ◽  
Azadeh Shakery ◽  
Heshaam Faili
Keyword(s):  
Sentiment Analysis ◽  
Induction Method ◽  
Non Parametric

scholarly journals Cooking Is Creating Emotion: A Study on Hinglish Sentiments of Youtube Cookery Channels Using Semi-Supervised Approach

2019 ◽  
Vol 3 (3) ◽  
pp. 37 ◽  
Author(s):  
Gagandeep Kaur ◽  
Abhishek Kaushik ◽  
Shubham Sharma
Keyword(s):  
Social Media ◽  
Logistic Regression ◽  
Unsupervised Learning ◽  
Sentiment Analysis ◽  
Learning Algorithms ◽  
Term Frequency ◽  
Learning Technique ◽  
Non Parametric

The success of Youtube has attracted a lot of users, which results in an increase of the number of comments present on Youtube channels. By analyzing those comments we could provide insight to the Youtubers that would help them to deliver better quality. Youtube is very popular in India. A majority of the population in India speak and write a mixture of two languages known as Hinglish for casual communication on social media. Our study focuses on the sentiment analysis of Hinglish comments on cookery channels. The unsupervised learning technique DBSCAN was employed in our work to find the different patterns in the comments data. We have modelled and evaluated both parametric and non-parametric learning algorithms. Logistic regression with the term frequency vectorizer gave 74.01% accuracy in Nisha Madulika’s dataset and 75.37% accuracy in Kabita’s Kitchen dataset. Each classifier is statistically tested in our study.

Study of Sentiment of Governor's Election Opinion in 2018

2018 ◽  
pp. 231-238
Author(s):  
Agung Eddy Suryo Saputro ◽  
Khairil Anwar Notodiputro ◽  
Indahwati A
Keyword(s):  
Sentiment Analysis ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Addition Method ◽  
Sentiment Mining ◽  
Positive Sentiment ◽  
Trending Topics ◽  
Election News

In 2018, Indonesia implemented a Governor's Election which included 17 provinces. For several months before the Election, news and opinions regarding the Governor's Election were often trending topics on Twitter. This study aims to describe the results of sentiment mining and determine the best method for predicting sentiment classes. Sentiment mining is based on Lexicon. While the methods used for sentiment analysis are Naive Bayes and C5.0. The results showed that the percentage of positive sentiment in 17 provinces was greater than the negative and neutral sentiments. In addition, method C5.0 produces a better prediction than Naive Bayes.

An historical analysis of species references in American English

Corpora ◽  
2019 ◽  
Vol 14 (3) ◽  
pp. 327-349
Author(s):  
Craig Frayne
Keyword(s):  
Environmental Change ◽  
Sentiment Analysis ◽  
Quantitative Methods ◽  
English Language ◽  
Language Use ◽  
American English ◽  
Historical Analysis ◽  
The Past ◽  
Corpus Studies ◽  
Google Books

This study uses the two largest available American English language corpora, Google Books and the Corpus of Historical American English (coha), to investigate relations between ecology and language. The paper introduces ecolinguistics as a promising theme for corpus research. While some previous ecolinguistic research has used corpus approaches, there is a case to be made for quantitative methods that draw on larger datasets. Building on other corpus studies that have made connections between language use and environmental change, this paper investigates whether linguistic references to other species have changed in the past two centuries and, if so, how. The methodology consists of two main parts: an examination of the frequency of common names of species followed by aspect-level sentiment analysis of concordance lines. Results point to both opportunities and challenges associated with applying corpus methods to ecolinguistc research.

ESTIMATION OF PRESSURE DROP FOR NON-NEWTONIAN LIQUID FLOW THROUGH BENDS USING ADAPTIVE NON-PARAMETRIC MODEL

2020 ◽  
Vol 47 (1) ◽  
pp. 59-69
Author(s):  
Suman Debnath ◽  
Anirban Banik ◽  
Tarun Kanti Bandyopadhyay ◽  
Mrinmoy Majumder ◽  
Apu Kumar Saha
Keyword(s):  
Pressure Drop ◽  
Liquid Flow ◽  
Parametric Model ◽  
Newtonian Liquid ◽  
Flow Through ◽  
Non Parametric
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