TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding (code & data)

Node Embeddings in Dynamic Graphs

Collect and process real time twitter data plotting various metrics like volume , proportion, sentiment. Analyze tweet node networks and map them geographically.

Temporal Walk Based Centrality Metric for Graph Streams

A gathering of digital methods recipes for research, teaching and collaborations from across the Public Data Lab.

Build a classifier to classify anti-national tweets from normal tweets based on the Khalistan movement.

Finding similarity index of a community in the twitter network using multiple views through inter-graph random walk kernel (IRWK).

🔍 This project is about searching the twitter for Soccer Prediction using popular keywords and applying sentiment analysis on the data.

Codes and data necessary to reproduce the results of the article K. Shyrokykh, M. Girnyk and L. Dellmuth, "Short Text Classification with Machine Learning in the Social Sciences: The Case of Climate Change on Twitter," submitted.

A Bidirectional LSTM model to classify whether a given tweet talks about a real disaster or not. This was my project in "CSC 522: Automated Learning and Data Analysis" course at NC State University.

Utility python package for RG17 and UO17 Twitter tennis data sets.

Twitter Sentiment Analysis

Analysing Twitter data to identify urban issues

In this project, I have explored the world of tweet analysis in the case of two European universities: University of Tartu and Lund University.

A repository with Twitter data and tweet classifiers using several machine learning approaches to measure the accuracy and performance of the approaches on classifying tweets.🐧

Under the broad research question: What are the impact of COVID-19 in ones life? Our team collected Twitter data to answer research hypothesis, producing models, and have a better understanding of the factors that influence one's reaction to the global pandemic.

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Twitter Semantic Data Mining for Harvey Hurricane Credible Event Detection

R code, markdown document, and Gephi files used to create a social network analysis project examining three information operations removed from Twitter in 2021.

Explore your Twitter activity with R: Sentiment Analysis and Data Visualization. How to analyze your Twitter account (or any account), discover your habits and sentiments with the "rtweet" package and NLP.

R code and markdown documents used to create a data analytics project examining three information operations removed from Twitter in 2021.

Script used in the Social Network Analysis course (Parking behavior Analysis, Project 12)

Tweet similarity ranking using Cosine Similarity with TF-IDF vector and BoW vector.

Twitter is one of the most used data sources for data analysis. The reason is that it’s open and free to collect unless you subscribe to the paid version one. Besides, it’s pretty simple to collect data from it.

Exploring #elxn43 Twitter data

This project includes Twitter Social Media Analytics, Facebook Graph Analysis and News API Data Analysis. See the final report for full understanding.

Exploratory Data Analysis with data cleaning, visualization, and insights for better understanding of datasets.

Getting started with Twitter data analysis.

The project focuses on sentiment analysis of tweets, categorizing them as positive, negative, or neutral to gauge public sentiment, with applications in market trends, election forecasts, and socio-economic predictions.