Internet traffic search and ethnic relations in russia
Download
1 / 34

Internet Traffic Search and Ethnic Relations in Russia - PowerPoint PPT Presentation


  • 296 Views
  • Uploaded on

Internet Traffic Search and Ethnic Relations in Russia. The Promise. Jeremy Ginsberg, Matthew H. Mohebbi, Rajan S. Patel, Lynnette Brammer, Mark S. Smolinski &  Larry Brilliant, “Detecting influenza epidemics using search engine query data,” Nature Vol 457, 19 February 2009

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Internet Traffic Search and Ethnic Relations in Russia' - erika


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

The promise l.jpg
The Promise

Jeremy Ginsberg, Matthew H.

Mohebbi, Rajan S. Patel, Lynnette

Brammer, Mark S. Smolinski & 

Larry Brilliant, “Detecting influenza

epidemics using search engine query

data,” Nature Vol 457, 19 February

2009

  • Developed a method to analyze a large volume of Google queries to detect social behavior

  • Improved early detection of social behavior

    http://dx.doi.org/10.1038/nature07634


Key components of the study l.jpg
Key components of the study

  • Google Trends: Internet search traffic measurement

  • Search query database: including IP addresses associated with each query

  • Prior years’ hard data on the behavior of interest (CDC)

  • Automated query-selection process: Identification of 45 highest-scoring search queries that fit the data from prior years

    • linear regression with 4-fold cross validation

  • Regional data aggregation: Maximizing fit probability and minimizing false positives

    • fit models to four 96-point subsets of the 128 points in each region.

  • Final model fitting: Tests in later years and for each individual state


Key lessons l.jpg
Key lessons

  • Sensitivity to the nature of social behavior

  • Sensitivity to variation across regions

  • Sensitivity to variation over time

  • Multiple measures

  • Data reduction


Applications for ethnic conflict research building block 1 search engines traffic calculators l.jpg
Applications for Ethnic Conflict ResearchBuilding Block 1:Search Engines & Traffic Calculators


Applications for ethnic conflict research building block 2 search query sources l.jpg
Applications for Ethnic Conflict ResearchBuilding Block 2:Search Query Sources


Slide18 l.jpg
SOVA Information-Analytical Center Project: “The Language of Hate in the Mass Media”http://xeno.sova-center.ru/213716E/21398CB


And other xenophobic websites l.jpg
ДПНИ of Hate in the Mass Media” and other xenophobic websites


Islamist radical websites l.jpg
Islamist Radical Websites of Hate in the Mass Media”


Other sources l.jpg
Other sources of Hate in the Mass Media”

  • Internet buzz: chat forums, blogs

  • Tube traffic: cell phone clips, provocative song titles, video posts

  • Yandex search spin-offs (trends by words)

  • Focus groups

  • Expert groups


Applications for ethnic conflict research building block 3 behavioral data sources l.jpg
Applications for Ethnic Conflict Research of Hate in the Mass Media”Building Block 3:Behavioral Data Sources


Violence data l.jpg
Violence Data of Hate in the Mass Media”

  • SOVA Center (xenophobic violence; systemic interethnic communal violence)

  • UCSJ: Anti-Semitism

  • Кавказский узел (хроники по Ингушетии, Дагестану, Чечне)

  • Voinenet.com (weekly event summaries across the North Caucasus)

  • Data on protest attendance (police, HR NGOs)

  • GEDS archives (UMD)


Slide27 l.jpg

Voting of Hate in the Mass Media”datahttp://www.vybory.izbirkom.ru/region/region/izbirkom?action=show&root=1&tvd=100100021960186&vrn=100100021960181&region=0&global=1&sub_region=0&prver=0&pronetvd=null&vibid=100100021960186&type=233


Potentially trackable phenomena l.jpg
Potentially trackable phenomena of Hate in the Mass Media”

  • Mobilization:

    • Xenophobic group names; party names; leader names; event names

  • Intergroup hostility

    • Expressions of hate (derogatory group epithets)

  • Violence:

    • Proxies (weapons purchase, martial arts clubs, extremist forums names)

  • Minority groups’ resistance:

    • Specific ethnic group names + rights; HR NGOs; defense lawyers names, etc

  • Trust in government/state capacity:

    • Legal texts, statutes (Art. 282), police measures