Description
Tweets can provide an informative pulse of what is being said on various public subjects. Even though tweets are short messages, their quantity, rhythms, and conversational structures are a way to understand a general opinion. One challenging aspect for monitoring near real-time updates is that we need to visually integrate the incoming data in the visual representation of data that has already arrived. This challenge arises for example during a meeting or a TV show, but also during a major event like presidential elections. To visualize Twitter streams during one such events, the 2012 French presidential election, we developed a web-based visualization called Bubble-t. It addresses the challenges of real-time visual update by using a particle system to fill in a bar chart. Each particle is a new piece of information that we refer to as a “token” (in this context, a Tweet). Each bar corresponds to a presidential candidate. Therefore, once a tweet is sent about a candidate, it is transformed into a token that is thrown into the candidate’s bar. By accumulation, the columns are progressively filled in by the tokens. When a column is full, the n tweets that first arrived are flushed out of their column. We mapped the Twitter user’s avatar to the token for additional informations and to further engage viewers. A static bar chart at the bottom captures all tweets during two different time periods (7days or 24hours). The application received an award at the Google Dataviz 2012 challenge. Up to 81 273 unique visitors browsed the website in 6 months time. The average visit duration was 4min 21s, which is long. We received positive feedback from Twitter users with morethan 1 800 tweets embedding the URL. This work also received attention from some national and authoritative media such as newspapers and radio. We also informally observed unexpected reaction from users. When the visualization was publicly presented, the audience in the room sent tweets, not only to test the system but also to show or see their own avatar inside the chart. Despite these successes we also identified several issues:(p1) The transition between the bar holding the tokens and the static chart at the bottom is not continuous. The time windows in which the token remain inside the bar is short due to the limited amount of screen space. The exploration of detail for aggregated tweets (in bars) is currently not possible.
Papers
Huron, S., Vuillemot, R., and Fekete, J. 2012. Towards Visual Sedimentation. Poster at Infovis'12 (Seattle, USA, October 14 - 19, 2012).
Award
- Google Data Viz 2012
News cover
Contacts
- Samuel Huron, INRIA and IRI
- Romain Vuillemot, INRIA
- Jean Daniel Fekete, INRIA
Acknowledgement
We thank CINEGIFT DGCIS project and ANR Periplus for the fund- ing; And also Google who hosted some of our case studies; Also the IRI team: Nicolas Sauret, Raphael Velt, Yves Marie Haussonne, Vincent Puig.