Twitter Trends

Twitter Trends is a web-based application that automatically detects and analyzes emerging topics in real time through hashtags and user mentions in tweets. Twitter being the major microblogging service is a reliable source for trends detection. The project involved extracting live streaming tweets, processing them to find top hashtags and user mentions and displaying details for each trending topic using trends graph, live tweets and summary of related articles. It also included Topic Modelling and Entity Categorization to classify the tweets and extract valuable information about its contents and find similar tweets and related articles and URLs. A trending topic is represented as a word cloud created from set of keywords (hashtags or user mentions) that belong to that topic. Thus this application provides the required information to get an overhaul of the topics which are trending at that particular time. This data can be used to support social analysis, finance, marketing or news tracking.

Project Name	Stars	Most Recent Commit	Open Issues	License	Language
Twitter Sentiment Visualisation	189	6 months ago	8		CoffeeScript
🌍 Sentiment analysis over real-time social media data, rendering live charts to visualise trends
Data Science Portfolio	125	5 years ago			Jupyter Notebook
A Portfolio of my Data Science Projects
Cloudberry	89	a year ago	2		Scala
Big Data Visualization
Tweeview	83	2 years ago	5	mit	JavaScript
A Tree View For Tweets
Turkish Tweets Sentiment Analysis	52	6 months ago	1		Jupyter Notebook
This sentiment analysis project determines whether the tweets posted in the Turkish language on Twitter are positive or negative.
Twitter Trends	52	7 years ago			Python
Twitter Trends is a web-based application that automatically detects and analyzes emerging topics in real time through hashtags and user mentions in tweets. Twitter being the major microblogging service is a reliable source for trends detection. The project involved extracting live streaming tweets, processing them to find top hashtags and user mentions and displaying details for each trending topic using trends graph, live tweets and summary of related articles. It also included Topic Modelling and Entity Categorization to classify the tweets and extract valuable information about its contents and find similar tweets and related articles and URLs. A trending topic is represented as a word cloud created from set of keywords (hashtags or user mentions) that belong to that topic. Thus this application provides the required information to get an overhaul of the topics which are trending at that particular time. This data can be used to support social analysis, finance, marketing or news tracking.
Pubnub Live Twitter Dashboard	27	7 years ago	2	mit	Python
Analyze sentiment from tweets and display it on an interactive dashboard
Trumpogram	18	7 years ago		mit	Python
The World, according to Donald Trump
Twitto_be	12	a year ago	14	other	EJS
twitto_be is a real-time tweets analytics dashboard
Twitter Sentiment Analysis	12	5 years ago		gpl-3.0	Jupyter Notebook
It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization