@inproceedings{d8fa6a9439984e7fb00c13776ef358db,
title = "GeoHashViz: Interactive analytics for mapping spatiotemporal diffusion of twitter hashtags",
abstract = "Since its birth in 2006, Twitter has evolved to a multi- purpose social media that attracts hundreds of millions of users to share their activities and ideas on a daily basis. The potential of capturing fine-grained activity log of users, combined with ever increasing geographical information derived from GPS-enabled devices, has made Twitter data a valuable source for spatiotemporal analysis of human activities. One of the early innovations of Twitter is the use of hash- Tag as a unique tagging mechanism to provide additional information about a user post. From its emergence in late 2007, hashtags have been used extensively to express ideas, group tweets and report events among Twitter users. The increasing popularity of hashtags, in addition to their simple and concise structure, has inspired multiple recent studies to propose hashtag as a medium to assess diffusion of ideas in a virtual world. Studying collective eFFort of users in making a hashtag go viral can shed light on the complex process of idea diffusion that involves psychological, sociological and geographical elements.",
keywords = "Cybergis, Geohashviz, Hadoop, Interactive visualization, Social media",
author = "Kiumars Soltani and Aditya Parameswaran and Shaowen Wang",
note = "Publisher Copyright: Copyright {\textcopyright} 2015 ACM. {\textcopyright} 2015 Copyright held by the owner/author(s).; 4th Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2015 ; Conference date: 26-07-2015 Through 30-07-2015",
year = "2015",
month = jul,
day = "26",
doi = "10.1145/1235",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "Proceedings of the XSEDE 2015 Conference",
address = "United States",
}