This repository contains independent project on Social Media Analytics to identify key predictors of social influence.
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Updated
Aug 13, 2020 - Jupyter Notebook
This repository contains independent project on Social Media Analytics to identify key predictors of social influence.
Taking a look at data of 1.6 million twitter users and drawing useful insights while exploring interesting patterns visualized with concise plots. The techniques used include text mining, sentimental analysis, probability, time series analysis and Hierarchical clustering on text/words using R.
A social media analytical tool that provides the useful insights and meaningful stats that helps in the enhancing your social media presence.
Social Media Themes
Semester 8
Social Media Analytics by Python on Biden and Trump's Twitter
Gives your customer's tweets, the sentiment of those tweets, and an interface for you to reply to them. Also, some analytics about your customers
This project involves helping a social media company better understand its user base & behavior on its platform.
This project aims to perform a social network and content analysis relatively to the r/marvelstudios subreddit from the popular online discussion forum Reddit. Report and project presentation are in english.
Here you can find Sentiment Analysis, NamedEntity Recognition, Social Media Analysis and Topic Modeling. Some of which are completed using NLP.
Social Lead Generator is an analytical tool for analyzing Twitter post statistics. This supports trending posts statistics.
This repository is for the analysis presented in poster format at the 2020 ASA-CSSA-SSSA Virtual Meeting around social media engagement habits of farmers.
machine learning project designed to analyze Instagram comments for sentiment detection, question identification, and topic modeling. Utilizing algorithms such as LDA, LSA, NMF, and BERT, CommentAnalyzer provides valuable insights into user interactions, helping brands and researchers understand audience sentiments and trends.
Code for the paper : Ensembles of Transformers and Large Language Models for Medical Text Classification
This project focuses on extracting and analyzing social media data from Reddit to uncover meaningful insights . The goal is to help marketing analysts understand trending topics, audience sentiment, and engagement patterns. By examining these insights, marketers can make data-driven decisions to enhance campaign strategies and improve engagement.
Identifying most popular programming language and technology on GitHub
This project aims to analyze the influencer journey of Robin Sharma, focusing on his social media activities across YouTube, LinkedIn, and Instagram. By extracting data using the YouTube API and manually collecting data from LinkedIn and Instagram, we provide a detailed analysis of his posts, engagement, and costs.
Analysis of Instagram Post Engagement through Topic Modeling
Analysis of unstructured data (text) with Python
Sentiment labels on Malaysian tweets talking about social distancing and physical distancing
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