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AFINN-based sentiment analysis for Node.js.
plugin to detect sentiment
Sentiment analysis based on afinn-165, emojis and some enhancements.
Sentiment Analysis of a Twitter Topic with Spark Structured Streaming
Análisis de sentimientos y visualización de datos con R, de conversaciones de WhatsApp, segunda parte. Uso de librería rwhatsapp.
Dart Sentiment is a dart module that uses the AFINN-165 wordlist and Emoji Sentiment Ranking to perform sentiment analysis on arbitrary blocks of input text.
sentiment analysis on quora answers based on word frequency [Deprecated]
Analyzing yelp dataset ==> https://www.yelp.com/dataset_challenge
Analyzing yelp dataset ==> https://www.yelp.com/dataset_challenge
Our goal in this group project is to apply NLP and other features from Yelp reviews into a model that outputs a new 5-star-rating, so that there is less discrepancy between reviews and star ratings. In order to make our model more robust, we will also incorporate new user star-ratings based on reviews read (meaning that someone who did not write the review gives a star-rating based on the review text alone) into our model so that it better reflects the review sentiment. We used multiple ML models, including: Naive Bayes, k-NN, K-Means, LSTM, N-Gram, TD-IDF and Linear Regression
Sentiment Analysis in Javascript using the various lexicons including AFINN-165, VADER, NRC Word-Emotion Association, Bing and Loughran-McDonald
AFINN for Indonesian Tales Classification
:performing_arts: Score sentences in a source text by POSITIVE or NEGATIVE sentiment; find best and worst sentences; plot sentiment on graphs in various ways
Automated IRC client which can connect to Twitch chat and analyse the current sentiment and dominant emotions in real-time.
Utilizando-se da linguagem R, o artigo apresenta uma análise da obra de Raul Seixas por meio da implamentação da API 'Spotifyr' e da função 'getsentiments()' do pacote tidytext.
Sentiment analysis of twitter users tweets by their usernames using AFINN.
A web scraping and sentiment data analysis of 707 Star Trek episodes, including The Original Series, The Animated Series, The Next Generation, Deep Space Nine, Voyager, and Enterprise.
Sentiment analysis in Kotlin.
Text miner, polarity rater with results between -100% and +100%
The goal of this project was build recommender systems using K-means and ALS based on the average ratings. It recommends similar books, recommends author based on a book title, recommends high rated books of the author.
The objective of the project is to detect the underlying sentiments of the product reviews. Classifying the reviews as positive, negative and neutral helps to determine the overall emotion behind the product and assist business strategies.
Experiments with web crawling, scraping, and indexing a collection of web documents. Clustering the indexed data with k-means algorithm. Each resulting cluster is assigned a sentiment score using AFINN - a sentiment analysis script.
This work is a text analysis in R based on the NASA data found in: https://data.nasa.gov/data.json . The text analysis is based in different steps starting with lexicons. Further investigating positive and negative sentiments on a world cloud . Also, correlations between words are analysed.
This project aims to implement the result of the sentence-level and word-level polarity of a given text.
Twitter semisupervised sentiment analysis with AFINN
Developed a Python program that scrapes tweets off Twitter using twint, based on the user’s input and exports the data as CSV. Extracted and analyzed sentiments using Afinn to examine how positive or negative the tweets are, using Matplotlib to display them on a pie chart.+more