Sentiment Sweep

Recently I developed and published an opensource web app that uses data from Twitter combined with sentiment analysis and emotion detection to create a series of data visualisations to illustrate the happy and less happy locations, topics and times....

The Final Product

Live application: http://sentiment-sweep.com/


The Aim

1. To make the uncomprehendable mass of Twitter data that available for many topic, accessible, clear and understandable for users.
2. To develop a new, faster more efficient method of calculating sentiment on the fly.
3. To use only opensource resources (and many of them!), and to then document and publish all code and findings from results back to the opensource comunity via GitHub.
4. To allow businesses and individuals to analyse the good/ bad points about what people are saying about their product or brand.

This primarily involved the research and development of a sentiment analysis module, and the implementation of it on real-time social media data, to generate a series of live visual representations of sentiment towards a specific topic or by location in order to find trends.


Screenshots

There are some screenshots of the various data visualisations here: 
https://github.com/Lissy93/twitter-sentiment-visualisation/tree/dev/docs/screenshots



Tech Stack

There is so much really cool new technologies (languages, libraries, API's, dev tools, platforms....) published opensource all the time! And I wanted this project to utilize and build upon many of these awesome projects! Below is a summary of the main tech stack:



Published Node Modules

Several open sauce node modules have been developed and published on npm as part of this project
  • sentiment-analysis - useses the AFINN-111 word list to calculate overall sentiment of a sentence
  • fetch-tweets - fetches tweets from Twitter based on topic, location, timeframe or combination
  • stream-tweets - streams live Tweets in real-time
  • remove-words - removes all non-key words from a string sentence
  • place-lookup - finds the latitude and longitude for any fuzzy place name using the Google Places API
  • hp-haven-sentiment-analysis - A Node.js client library for HP Haven OnDemand Sentiment Analysis module
  • haven-entity-extraction - Node.js client for HP Haven OnDemand Entity Extraction
  • tweet-location - calculates the location from geo-tagged Tweets using the Twitter Geo API
  • find-region-from-location - given a latitude and longitude calculates which region that point belongs in

Documentation

Thorough documentation of opensource projects is very important to ensure future maintainability, and to allow other developers to use the code in their projects, or to contribute.

The documentation can be viewed at: https://github.com/Lissy93/twitter-sentiment-visualisation/tree/dev/docs

Below are links to each of the key documentation articles written as part of the project 


Project Information

Project Planning

Development Documentation

Research




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Hack Zurich 2016

Europes biggest 40 hour non-stop hacking marathon, HackZurich 2016 had  800+ Attendees from around the globe, 500+ hackers, hundreds of submissions, and 3.6 tons of food. Big name sponsors (including Google, Kyak, Adobe, Samsung, Bosch, Microsoft and loads way more) ensured that event was an awesome one. Plenty of funding for a great venue, tons (literally) of food, a swimming pool worth of RedBull and proper coffee, not to mention enough swag to not need to go shopping for the next year!









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