Big data refers to large, complex datasets that are difficult to process using traditional tools. Internews uses big data and data verification techniques to analyze large amounts of related information and spot trends. Data verification involves falsifying or verifying the context, content, and source of information through methods like crowdsourcing, engagement with sources, and media authentication to establish the truth. The challenge is how to effectively verify crowdsourced information and use big data to provide decision makers with reliable insights.

1. Big Data and Data Verification
What does big data mean to Internews?

2. What is Big Data?
In information technology, big data is a collection of data sets so
large and complex that it becomes difficult to process using
“normal” database management tools or traditional data
processing applications. The challenges of processing this data
include how to capture, to curate, to storage, to search, to
share, to analyze, and to visualize it. The appeal to use larger data
sets is driven by the additional information available from
analysis of a single large set of related data, as compared to
separate smaller sets with the same total amount of
data, allowing correlations to be found to spot trends, determine
quality of research, run preventive analysis, spot
correlations, model risks, and determine real-time impacts of
events.

6. WHAT DOES BIG DATA HAS TO
DO WITH INTERNEWS?

9. Data verification

12. ELECTUA.ORG

16. Falsifying/Verifying
the context
Falsifying/Verifying
the content
Falsifying/Verifying the
source

17. Social Media ID
ID of the
Content on the
Social media
Crowdsourcing
Direct
engagement
Media
authentication
Verification
of the
source
Timing
Influence
Location
ID of the
Network
ID of the
trusting
network

18. Language
Crowdsourcing
Content ID on
Social Network
Pictures/Video
Verification
of the
content
Time and
place
Triangulation
Follow up with
source

19. Factual
context
Crowdsourcing
Verification
the context
Time and
Location
Global Context

22. Different technics to verify
1.
2.
3.
4.
Separated Trusted and untrusted sources
Trusted sources verify untrusted sources
Verification protocols and technics
Putting the burden of the verification process
on the user

23. Falsification is always
possible…
..but so is verification!

24. +
=
TRUTH….?

25. The question is not if we can
verify crowdsourced information
or use big data in our work, the
question is how do we make the
verified data
for decision makers

26. THANK YOU
ANAHI AYALA IACUCCI
AAYALA@INTERNEWS.ORG
@INFO_INNOVATION
@ANAHI_AYALA