TwitterExplorer-Energy: Data

NOTE: Dataset is encrypted. Access here.
To obtain decryption key please contact: Dr. Neil Rubens rubens at activeintelligence.org OR Dr. Martha G. Russell martha.russell at stanford.edu.

Energy-Behaviors Twitter Dataset

SUMMARY:

2,472,900 tweets
18,338 hashtags (w/ occurrence of 3 or more)
Date Range: 3.Sep.2010 - Jan.3.2011 (4 months)
Data Collection Frequency: daily snapshots
Keywords: keywords related to energy saving behaviors (see keywords.txt).

DESCRIPTION:

This dataset was constructed as a part of the "Social Media Analytics for Monitoring and Changing Energy Consumption Behavior" initiative of the Stanford ARPAe project. For more details please refer to: M. G. Russell, J. Flora, M. Strohmaier, J. Poschko, R. Perez, N. Rubens. Semantic Analysis of Energy-Related Conversations in Social Media: A Twitter Case Study. International Conference of Persuasive Technology (Persuasive 2011), Columbus, OH, USA, Jun.2011.

The initial purpose of constructing of this dataset was to assist in understanding the role of social media in changing consumer’s energy behavior. It is released publicly to encourage creation of new insights on how to change consumers' energy behaviors.

Data was acquired on a daily basis by utilizing the NodeXL Twitter Importer module *xl1, which captured the latest messages containing energy related keywords (see keywords.txt). The eco-linguistic keywords used to collect the tweets was developed at Stanford University by Drs. June Flora, Carrie Armel, and Martha Russell, under sponsorship from the US Advanced Research Projects Agency for Energy, and Media X at Stanford University.

*xl1
NodeXL Twitter Importer module creates a separate file for each of the keywords. This dataset contains amalgamation of these files. Some of the tweets are duplicated in the dataset, since a tweet could be captured by several keyword-based files.

FOR MORE INFORMATION:

M. G. Russell, J. Flora, M. Strohmaier, J. Poschko, R. Perez, N. Rubens. Semantic Analysis of Energy-Related Conversations in Social Media: A Twitter Case Study. International Conference of Persuasive Technology (Persuasive 2011), Columbus, OH, USA, Jun.2011.

Website of the Change Energy Behavior Initiative: http://mediax.stanford.edu/changeeb.html

Web-interface to the tweetonomy network based on this dataset: http://energy.twex.poeschko.com

This research is a collaboration among:

• the Stanford ARPAe project to develop an ecolinguistic taxonomy and describe the evolution of communities of awareness, interest, influence and action: Martha G. Russell, June Flora and Carrie Armel

• the Active Intelligence Laboratory for data collection and analysis: Neil Rubens and Rafael Perez

• the Agents and Social Computation group at Graz University of Technology, led by Markus Strohmaier, with students Claudia Wagner and Jan Poeschko.

The objective of this collaboration is to further develop and apply these frameworks, concepts and tools in the context of a particular domain, using social media as a new, emerging media for analyzing and characterizing energy consumption behavior on Twitter. In bringing together two largely unconnected areas of research, this project has implications for, for example, identifying new ways of tracking public opinion related to energy consumption and for analyzing domain-specific, user generated content on social media platforms. Insights are intended to contribute to the development and application of a social media analysis framework for studying energy consumption behavior on Twitter and related social media platforms.

For more information, contact Martha Russell.