Tweether: A visualization tool displaying correlation of weather to tweets

Shruti Daggumati, Igor Soares, Jieting Wu, David Cao, Hongfeng Yu, Jun Wang

Research output: Contribution to journalConference articlepeer-review


As the generation of social media, we can instantly express how our day is going; however, unknowingly the weather can play a key role in how we are feeling. The weather may dictate our lives regardless of what may be happening. The relationship between weather and mood has been immensely studied to show that the weather does play a major factor regarding our emotions. However, how we visualize the relationship and influence between weather and human emotions remains an interesting question. Based on the natural correlation between weather and mood, we propose Tweether, a real-Time weather and tweet visualization tool, to see how Twitter users feel regarding the weather they experience. Our visualization displays a current reflection of emotions in a set of select geographic regions and also predicts possible emotions in these regions in response to the weather forecast. The visualization uses multiple layers to show the connection between geolocations, weather, and emotions. By aggregating multiple users with emotions, we create an aesthetic design in a 3D manner that is relatively free of visual clutter and it is simple to understand the relationships between weather and emotions.

Original languageEnglish (US)
Article numberVDA-497
JournalIS and T International Symposium on Electronic Imaging Science and Technology
StatePublished - 2016
Event23rd Visualization and Data Analysis Conference, VDA 2016 - San Francisco, United States
Duration: Feb 14 2016Feb 18 2016

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics


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