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Embassies burning: toward a near-real-time assessment of social media using geo-temporal dynamic network analytics

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Abstract

Effective crisis response requires rapid assessment of a situation in order to form actionable plans. Social media and traditional media are critical to this assessment. This paper describes a rapid ethnographic approach for extracting information from Twitter and news media and then assessing that information using dynamic network analysis techniques. Text mining high-dimensional network analytics and visualization are combined to provide an integrated approach to assessing large dynamic networks. This approach was used as the Benghazi consulate and the Egyptian embassy were attacked in 2012. This near-real-time assessment was set against a backdrop of ongoing data collection associated with the Arab Spring countries. This ongoing collection provided a baseline for Libya and Egypt against which the new data could be assessed. Herein, the outcome of that near-real-time assessment, the tools used, the lessons learned, and the results discovered are described. The same approach was used in other crisis events including SuperStorm Sandy, the Kenyan elections, from which examples are also drawn. We find that to be effective such analytics require the use of multiple media, deep dives into specific secondary issues, and a high-level assessment of not just who is doing what, but who is providing what information. Finally, we show the criticality of baseline data for interpreting the behavior during a crisis.

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Notes

  1. Additional results can be seen at www.pfeffer.at/sandy and www.casos.cs.cmu.edu/projects/kenya.

  2. For a demo of TweetTracker, see https://www.youtube.com/watch?v=1tZ4wnkEfaQ.

  3. Relevant keywords for the movie are as follows: basseley, bacile, the real life of Muhammad, innocence of Muslims, and Nakoula. The Arabic equivalents were also used.

  4. Relevant keywords for terrorism are as follows: terrorism, terrorist, al-qaeda, al qaeda, al-qaide, al qaide, alqaeda, zawahiri, and al-zawahiri. The Arabic equivalents were also used.

  5. To normalize the data, first the maximum number of articles for a day for every country was calculated. Then, the fraction of articles for every day by country relative to this maximum was calculated. Then, the values were added by day were added for all four countries, and the resulting value divided by 4 (the number of countries).

    This means that each country can have a value between 0 and 0.25 on any given day, e.g., Egypt has this day on February 1, 2011. If none of the other 3 countries has any coverage on this day, the sum stays around 0.25.On a day with lots of stuff in all country, this level goes up as the day is (relatively) important everywhere (maximum possible value would be 1.0 if there is a great deal of news coverage everywhere on the same day).

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Acknowledgments

This work was supported in part by the Office of Naval Research with support to CMU and ASU for social media exploitation, and social network based rapid ethnographic assessment, and to Netanomics for crisis mapping. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Office of Naval Research or the US Government.

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Authors and Affiliations

  1. Institute for Software Research, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Kathleen M. Carley & Jürgen Pfeffer

  2. Netanomics Inc., Pittsburgh, PA, USA

    Kathleen M. Carley

  3. Computer Science and Engineering, Arizona State University, Tempe, AZ, USA

    Fred Morstatter & Huan Liu

Authors
  1. Kathleen M. Carley
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  2. Jürgen Pfeffer
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  3. Fred Morstatter
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  4. Huan Liu
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Corresponding author

Correspondence to Kathleen M. Carley.

Additional information

This paper is invited as an extended version of Kathleen. M. Carley, Jürgen Pfeffer, Huan Liu, Fred Morstatter, Rebecca Goolsby, 2013, “Near Real Time Assessment of Social Media Using Geo-Temporal Network Analytics,” In Proceedings of 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), August 25–28, 2013, Niagra Falls, Canada.

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Carley, K.M., Pfeffer, J., Morstatter, F. et al. Embassies burning: toward a near-real-time assessment of social media using geo-temporal dynamic network analytics. Soc. Netw. Anal. Min. 4, 195 (2014). https://doi.org/10.1007/s13278-014-0195-3

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