watedu's starred repositories
deeplearning_by_diye
This a deep learning code for myself.
App-Reviews
Data Wrangling and Exploratory Analysis of Reviews data obtained from Google Play Store. Text pre-processing is done on the reviews using NLTK library and regular expressions.
AppReviewClassifier
App Review Classifier built on Sci-Kit Learn Classifiers to classify App Reviews
Search-Rank-Fraud-and-Malware-Detection-in-Google-Play
Fraudulent behaviors in Google Play, the most popular Android app market, fuel search rank abuse and malware proliferation. To identify malware, previous work has focused on app executable and permission analysis. In this paper, we introduce Fair Play, a novel system that discovers and leverages traces left behind by fraudsters, to detect both malware and apps subjected to search rank fraud. Fair Play correlates review activities and uniquely combines detected review relations with linguistic and behavioral signals gleaned from Google Play app data (87K apps, 2.9M reviews, and 2.4M reviewers, collected over half a year), in order to identify suspicious apps. Fair Play achieves over 95% accuracy in classifying gold standard datasets of malware, fraudulent and legitimate apps. We show that 75% of the identified malware apps engage in search rank fraud. Fair Play discovers hundreds of fraudulent apps that currently evade Google Bouncer’s detection technology. Fair Play also helped the discovery of more than 1,000reviews, reported for 193 apps that reveal a new type of coercive review campaign: users are harassed into writing positive reviews, and install and review other apps.
SentimentAnalysis
The sentiments of user reviews collected from YouTube videos, Google Play store apps, movies are analyzed using K Means, Support Vector Machine, Naïve Bayes and Decision Tree Classifiers.
Android-ApplicationSuccess-Prediction-and-Review-Analysis
A machine learning project which uses regression to determine app rating, classification to classify user review sentiment and clustering to identify relation between various app attributes.
touch-note-app-review-classification-web-app
An AI solution which cognitively able to detect(classify) reviews in fractions of seconds. hence, fewer human interventions, more precise, uniform results, and most importantly operational efficiency.
google-app-review-system
This is a machine learning and a data analysis project used for classifying the best and the worst app according to the user review.
Topic-Extraction-from-Mobile-App-Reviews
A Natural Language Processing based method to identify and classify topics from mobile application reviews.
bert-sentiment-app-reviews
BERT Sentiment classifer web app to classify real-world app reviews with PyTorch
review-classifier
Machine learning application to classify and identify the topics of reviews from App stores
App-Reviews-Classifier
Classifier algorithm using NLTK library to classify a review as a Bug, Feature, UserExperience or Rating.
AARClassifier
Android App Review Classifier
emotion-analysis-5
情感分析五分类
Android-App-Reviews-Dataset
Android App reviews Crawler and 10k dataset of positive and negative reviews
user_quality
Dataset for Software Evolution and Quality Improvement
becloma-info
Online Appendix of BECLOMA
AspectBasedSentimentAnalysis
Aspect Based Sentiment Analysis is a special type of sentiment analysis. In an explicit aspect, opinion is expressed on a target(opinion target), this aspect-polarity extraction is known as ABSA.
ai_challenger_2018_sentiment_analysis
Fine-grained Sentiment Analysis of User Reviews --- AI CHALLENGER 2018
Feature-based-opinion-mining
Extracting all the features of a product from its reviews, giving every feature a score (depending on the user reviews) and also ranking the reviews based on their usefulness