How Useful Is A Tweet?
iHub Research’s 3Vs of Crowdsourcing
Angela Crandall Nanjira Sambuli Chris Orwa
This research was funded by Canada’s International Development Research Centre.
Twitter: Some Facts and Figures
• Launched in 2006
• Approximately 550 million active users
• About 200 million monthly active users
• An average of 400 million tweets are sent
• 60% of the monthly active users log on using
a mobile device at least once every month
Twitter and the Tweeps
• Twitter…can be more of a news media than
even a social network (Kwak et al, 2010)
• Breaking news and coverage of real-time
events are all shared under the 140-character
• Twitter users search for up-to-the-second
information and updates on unfolding events
Twitter for Crowdsourcing.
Collecting information from the “crowd”
• Allows for a wide reach of people in inexpensive ways
• Large amounts of data can be obtained quickly, and
often in real time
• Not necessarily through tech, but nowadays most use
tech such as online or via mobile phone
• Crowdsourcing fosters citizen engagement with the
information—to dispute, conﬁrm, or acknowledge its
Mapping Kenyan Election Events,
Thanks to crowdsourcing!
What is there to (Twitter) crowdsourcing?
Viability: In what situation/events is crowdsourcing a
viable venture likely to oﬀer worthwhile results/
Validity: Does crowd-sourced information oﬀer a true
reﬂection of the reality on the ground?
Veriﬁcation: Is there a way in which we can verify
that the information provided through crowdsourcing
is indeed valid? If so, can the veriﬁcation process be
Crowdsourcing during an Election
• What, if any, particular conditions should be in place
for crowdsourcing of information to be viable during
an election period?
• Can crowd-sourced information be validated during
an election period? If so, what is the practical
implementation of doing so?
• How do diﬀerent crowdsourcing methods contribute
to the quality of information collected?
o Elections in Kenya have been noted to spark many
online conversations, especially with the continued
uptake of social media;
o Citizens have an important role to play to contribute
information from the ground;
o Existing election crowdsourcing initiatives (such as
Uchaguzi), but none use passive crowdsourcing;
o Research exists around crowdsourcing during
disasters, but does not yet exist around elections.
Why Crowdsourcing, Kenyan
Elections and #KoT
• #KoT have participated in crowdsourcing activities
severally, under hashtags such as #CarPoolKE,
#ﬁndfuel, #SomeoneTellCNN etc.
• Approximately 90,000 tweets generated during the
ﬁrst Kenyan Presidential Debates (as monitored
using popular hashtags)
• Election-campaigning was also digital
(Online) Passive Crowdsourcing
vs. Active Crowdsourcing
• Active – Open call made for participation
(e.g. Ushahidi’s Crowdmap).
• Passive – Sifting through content already
being generated (e.g. on Twitter/
Facebook) to capture relevant
What we did
Cross-comparison of diﬀerent media
o Traditional Media
o Data mining from Twitter
o Uchaguzi Crowdsourcing
First tweet by a government institution about
Mining Of Twitter Data without
Machine Learning is Not Feasible
90 hrs 100 270 days No No
4.5 hrs 400 27 days No In a very
6 mins, 1.5
12,208 Less than 1
From the Westgate Incident…
Mining tweets from the Westgate attack
manually has been labour-intensive, limiting us
to suﬃciently analysing the ﬁrst half hour
(12:38 PM – 1:18 PM GMT+ 3)
Further analysis into Twitter data from the
incident will require machine learning
o Kenyan social media content is rich with real-time
updates of happenings that might not be present in
mainstream media reports.
o Mining of crowd-sourced data appears to be high value
when one is looking for timely, local information.
o There are indeed considerations that are useful for
assessing and running an election-based crowdsourcing
The 3Vs Crowdsourcing
AVAILABLE FOR FREE DOWNLOAD HERE:
• Testing the 3V’s Framework on other election-
related crowdsourcing opportunities
• Move to real-time analysis of tweets
• Provide tools for verifying crowdsourced
• Integrate research to media practices
• Working with local media organizations to build a
useable tool for collecting real-time
newsworthy incidents from the crowd