Data Visualization

With increasing use of social networking and social media, visualising and analyzing that data across all formats has become extremely essential.

Authentication of Social Data

As the Washington DC area houses a large number of government as well as non-governmental organizations, the data analysis and security is extremely crucial. For example, twitter account of one of the leading presidential front-runner in US was hacked recently , and I believe that could have been easily avoided.

Statistics show that about 15% of Americans have never checked their social networking privacy and security account settings, and 85% of parents with teenage children ages 13-17 report that their child has a social networking site. Source

My idea #1

My initial idea was to authenticate social media with the touch of a fingerprint. Yes, social media has been evolved to such a stage that we need to involve biometrics now.

My approach

  • I tried to integrate a fingerprint sensor using Arduino Uno, and create a communication with Arduino Uno and Twitter.
  • I was able to accomplish my connection between Arduino Uno and Fingerprint sensor, and stored the creentials in a key-value pair.
  • However, I was unable to connect Twitter to an Arduino due to internet and potential firewall settings at the hackathon venue.
  • Hence, I was forced to drop the idea and focus on another idea.

My idea #2

My another idea was to analyze a company's or a person's Twitter account, and create a user-friendly interface where they can monitor their tweets/followers and media, providing statistics and graphical visualization.

However, I had again trouble using Twitter's API, and was unable to get one of the queries, and so I decided to analyze another social media platform.

Hence, I am now analyzing Instagram statistics, using python, HTML/JS, and other open source libraries.

The script analyzes and outputs data from past one year from the user's Instagram posts and provides information at different time interval ranging from hourly data to a year.

How I built it

I built it using Python, SQL, HTML, Javascript, CSS and various open source Python libraries.

Accomplishments that I am proud of

I am proud of what I accomplished at this 36-hour hackathon, as I exposed myself to different programming environments, and solved some of the crucial challenges, all by myself.

What's next for DataGram

  • I am planning on adding more functionalities and expand this to different social media platforms.
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