Class Projects - Spring 2014

Qwotd

Qwotd is a cross-browser extension that highlights passages in a news article that have been shared most frequently on Twitter.

Qwotd is a cross-browser extension that highlights passages in a news article that have been shared most frequently on Twitter.
What it does

Social media drives significant traffic to news websites, but once a reader arrives at an article, the social media interaction ends or at least pauses. Qwotd brings social media to article pages by highlighting passages quotes from the article that have been shared on Twitter.  Readers gain a better understanding of the social media conversation around an article, which enables them to contribute to the conversation with greater perspective. Readers are also provided with frequent tweets, hashtags, and user mentions.

The idea for Qwotd began as a tool for journalists and editors to analyze how their content was being perceived in real time. This would allow them to tailor follow-up articles and re-releases with better leads or headlines based on what readers were interested in. However, Qwotd grew into a tool to improve the reading experience of anyone who reads an article by giving him or her a better perspective of the global conversation.


How it works

When a reader visits an article, the browser extension calls the Qwotd API, which sits between the extension and the Twitter API.

The first time an article is accessed the Qwotd API searches Twitter for the URL and stores the results in a database, which significantly decreases lag time for future readers. It also scrubs the URL of any variables (such as those meant to track how many pages a user has visited or where they’ve come from), which gives Qwotd the greatest number of search results.

For each tweet returned, Twitter also includes the number of favorites and retweets, which Qwotd uses to rank tweets and show the most popular. Qwotd’s most distinctive feature is its parsing technology, which uses JavaScript and JQery to compare tweets to passages from the article and highlight them.


Next Steps
  • Website that would provide more information and metrics about articles.
  • Features that allow users to see articles and popular passages from their own social network.
  • Enable users to write tweets by highlighting passages from an article and sharing them on Twitter.

Connect

Student team:

Monisha Appalaraju, Frank Avino, and Chris Williams

Faculty guidance:

Larry Birnbaum and Rich Gordon

Acknowledgements: Sluice – a design proposal for the #SNDMakes Designathon held in Indianapolis — was the inspiration for this project.