Senti Lamp

Published

Introduction: Senti Lamp

Senti Lamp is a mood light that changes colour depending on the sentiment of tweets with a given keyword, in real-time.

Which problem do we solve?

It's hard to constantly look at your brand's digital Twitter dashboard.

Our solution...

A mood light to display the sentiment of tweets in an unobtrusive way.

How we did it?

With Intel Edison, we stream live Twitter data and deploy a machine learning algorithm to classify the tweets into positive and negative. We then aggregate the sentiment over time and output the value to RGB LED lights to transform it into a colour.

Step 1: Material and Tools

You will need...

Materials:

Intel Edison board

Tools:

Python

node

Step 2: Machine Learning

We train the machine learning algorithm on a laptop using Twitter data already included in Python nltk package. We save the algorithm into a file using pickle and copy it into Edison. We will call this algorithm on Edison to classify the tweets into positive and negative in real time.

The code to train the algorithm, train.py is here:

https://github.com/anna-dz/mood_lamp

Run it just once on your laptop and copy naivebayes.pickle and word_features.pickle files onto Edison.

Step 3: Data Processing on Edison

Code to stream data, calculate a sentiment value and output it into RGB light (and Intel IoT Analytics) is in scrape.py:

https://github.com/anna-dz/mood_lamp/blob/master/s...

Step 4: Front End

We have a website for keyword input (select keyword or hashtag to stream), which also displays some of the incoming tweets. It's hosted on Edison and written in node.js.

Step 5: Hardware

Step 6:

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    Cool looking lamp. Do you have any more pictures of the assembly process.