Geographical Diffusion of IT Trends

What is more popular on Twitter right now?

A visualization tool for performance trends

#Trendit is a web application that allows users to interact with each other based on latest trending topics across the world. A simple web application developed in Django with Twitter API integration for fetching trends and tweets relevant data.

An analysis of Berlin

Grabs current trends from Twitter and displays the sentiment as well as aggregates news articles associated with each trend

Code to stitch together multiple 90-day periods of Google Trends data (tldr: it doesn't work very well)

Find which news acticles Carleton students care about, with analyzation of trends

My high school capstone project, showcasing trends in web design

R Shiny app to monitor Real Time Trending Topics on Twitter.

A supervised Learning approach to find the trends on which the monsoon rainfall depends and its prediction.

A complete overview of the JavaScript landscape in 2016: trends about front-end and node.js frameworks, tooling... Available in English, Japanese and Chinese.

We are using YouTube videos to analyze and predict tags associated with each video using Machine Learning techniques and find interesting trends by performing sentiment analysis using Natural Language Processing on the top 10 trending videos in YouTube using title, description and comments.

A Ruby on Rails based web app to find tweets on topics of your choice.

Google Trends library for Go

A framework to take the songs heard using Spotify and shared on social to extract information about tracks, genres, users. SpotiSpy performs more than just visualization: it analyzes the kinds of songs, geolocalizes users, extracts the list of most listened songs, and so much more. Created with BIG help of @valentinarho.

This project analyses the sentiment level of any product and plots the total percentage of tweets which were liked and hated,along with various levels between them using social media data

Use time series and knowledge of the industry to find trends, seasonality, and movement in ordering to predict inventory requirements.