Scraping the Social Graph with Ushahidi and SwiftRiver

29
SCRAPING THE SOCIAL GRAPH CRISIS MONITORING WITH SOCIAL MEDIA Georgetown University [email protected] @jongos

description

As delivered by Jon Gosier at Georgetown University on June 28th.

Transcript of Scraping the Social Graph with Ushahidi and SwiftRiver

Page 1: Scraping the Social Graph with Ushahidi and SwiftRiver

SCRAPING THE SOCIAL GRAPHCRISIS MONITORING WITH SOCIAL MEDIA

Georgetown [email protected]

@jongos

Page 2: Scraping the Social Graph with Ushahidi and SwiftRiver

About UshahidiUshahidi is a free, open-source platform used for crowdsourcing and visualizing data geospatially. It was born out of the 2008 election unrest when founders Juliana Rotich, Erik Hersman, Ory Okolloh and David Kobia wanted to allow Kenyan citizens a way to SMS reports of incident to know what was occurring around them. This was one of the earliest uses of crowdsourcing for crisis response.

Notable UsesUshahidi has been deployed in major global crisis scenarios, allowing organizations to draw situational awareness from the crowd. To date it ’s been downloaded over 15,000 times.

Some of the more notable deployments include recently in Egypt, the Haiti earthquakes, the fires in Russia, the Queensland floods in Australia.

The ChallengeA s t h e a m o u n t s o f d a t a aggregated by Ushahidi users grows, they face a common problem. How do they effectively manage this realtime data? How can we help them discover credible and actionable info from the deluge of reports they’ll get from the public? The SwiftRiver initiative was created to begin to answer some of these questions for Ushahidi deployers.

Page 3: Scraping the Social Graph with Ushahidi and SwiftRiver
Page 4: Scraping the Social Graph with Ushahidi and SwiftRiver

USHAHIDI HAITI

Page 5: Scraping the Social Graph with Ushahidi and SwiftRiver

OILSPILL CRISIS MAP

Page 6: Scraping the Social Graph with Ushahidi and SwiftRiver

UCHAGUZI

Page 7: Scraping the Social Graph with Ushahidi and SwiftRiver

RUSSIAN FIRES “HELP MAP”

Page 8: Scraping the Social Graph with Ushahidi and SwiftRiver

PAKREPORT

Page 9: Scraping the Social Graph with Ushahidi and SwiftRiver

TUBESTRIKE CROWDMAP

Page 10: Scraping the Social Graph with Ushahidi and SwiftRiver

PRAGUEWATCH

Page 11: Scraping the Social Graph with Ushahidi and SwiftRiver

HARASSMAP

Page 12: Scraping the Social Graph with Ushahidi and SwiftRiver

U-SHAHID

Page 13: Scraping the Social Graph with Ushahidi and SwiftRiver

CHRISTCHURCH

Page 14: Scraping the Social Graph with Ushahidi and SwiftRiver

SINSAI.INFO

Page 15: Scraping the Social Graph with Ushahidi and SwiftRiver

“It’s not information overload. It’s filter failure.”

- Clay Shirky

Page 16: Scraping the Social Graph with Ushahidi and SwiftRiver

PLATFORM GOALS

Consider the context, relevance defined by the user

Offer an opt-in global database of trust and authority

Algorithms augment, but not define, human decision making

Work across media channels (Twitter, Email, Feeds, SMS)

Be accessible (offline/online/mobile)

Index massive amounts of the mobile/social web

Page 17: Scraping the Social Graph with Ushahidi and SwiftRiver

KNC AWARD & RIVER ID

final component of the veracity algorithm

needs to be able to scale massively

changing the backend (Hadoop & Mongo DB)

research by data scientists

use-cases at scale and iterative improvements

Page 18: Scraping the Social Graph with Ushahidi and SwiftRiver

THIS IS A DATA PROBLEM

Page 19: Scraping the Social Graph with Ushahidi and SwiftRiver
Page 20: Scraping the Social Graph with Ushahidi and SwiftRiver

PROGRESS

7,000+ downloads in 6 months

7,000+ API Users

100,000+ Lines of code

5 APIs and 2 Apps

Data Items Processed - 70,000,000 (liberal extrapolation)

Page 21: Scraping the Social Graph with Ushahidi and SwiftRiver
Page 22: Scraping the Social Graph with Ushahidi and SwiftRiver
Page 23: Scraping the Social Graph with Ushahidi and SwiftRiver

Sweeper - User Interface

Page 24: Scraping the Social Graph with Ushahidi and SwiftRiver

NETWORK DYNAMICS

Good crowdsourcing campaigns build upon the existing ties between people and their networks. There’s a natural mult-iplier, where the people in the original network become nodes for new networks and so on.

Page 25: Scraping the Social Graph with Ushahidi and SwiftRiver

❖ Participation is permission❖ Consent is not carte blanche❖ Clarity is critical❖ Trust is Earned or Burned❖ Transparency is hard to teach

EARNING TRUST

Page 26: Scraping the Social Graph with Ushahidi and SwiftRiver

❖ Protection of data is different than the protection of people/identity❖ Standards like HTTPS or SSL❖ Encryption❖ Anonymity is not a given (TOR Project)❖ The usual fail-points are still threats (weak passwords, compromised servers, careless employees)

PRIVACY

Page 27: Scraping the Social Graph with Ushahidi and SwiftRiver

❖ Verify factual occurrences (location, time, date)❖ Verify contributor identity (who?)❖ Verify contributor credentials

VALIDATION

Everything beyond these three points is an educated guess. Anyone looking to game the campaign will only be affective if they are able to compromise the aforementioned.

Page 28: Scraping the Social Graph with Ushahidi and SwiftRiver

❖ Ease of participation❖ Low risk of failure or shame❖ Social Capital ❖ Repute & Accolade❖ Barter❖ Strategic Spending ($)❖ Data Sharing❖ Altruism & Charity

MOTIVATION

Page 29: Scraping the Social Graph with Ushahidi and SwiftRiver

THANKS!Knight News Challenge

[email protected]@swiftriver