pheme veracity: the 4 th challenge of big...

PHEME http://www.pheme.eu

PHEME Veracity: The 4th Challenge of Big Data

Tomás Pariente [email protected]

@tpariente


Phemes & social media

• Memes are thematic motifs that spread through social media in ways analogous to genetic traits

• We coined the term phemes to add truthfulness and deception to the mix

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http://en.wikipedia.org/wiki/Pheme

PHEME focuses on a fourth crucial, but hitherto largely unstudied, challenge: Veracity

http://en.wikipedia.org/wiki/Pheme


Rumour analysis: The Problem

Now mostly manual

Rumours are challenging Some rumours could take hours, days, weeks or even months to die out

Ill-meaning humans can currently outsmart computers (and humans) and appear genuine


Rumour analysis: The Problem

Mike Brown shot by police in Ferguson We have different rumors emerging from the topic

We don’t know if they are true.

We see the spikes and sometimes they come back (different temporal dynamics)

We need to understand the overall conversation to see the different points of view and how the rumours go forward


Social Media is Rife with Phemes


From manual to automatic We are investigating... Ontologies for modelling phemes

Use a priori knowledge (LOD) and reasoning to detect contradictions

Model phemes spread across media, social networks, and time

Conversational analysis

Real-time rumour classification

Pheme visualisation to support veracity checking: media maps, impact maps, geographical maps…


PatientsLikeMe

Cross-Media Content Linking,

Spatio-Temporal

Grounding

Multilingual LOD-Based

IE and Opinion Mining

Rumour Detection

And Veracity

Classification

USE CASES

Veracity Intelligence In Patient

Care

Digital Journalism

Linked Open Data Rumour Ontologies & Reasoning (GraphDB)

Historical Data

Archive

PHEME Visual

Analytics Dashboard

Social Context Models

Trust, Authority, Implicit

Networks

Technology Outcome: Open Source Computational Framework

...

…

PHEME VERACITY INTELLIGENCE FRAMEWORK

PHEME http://www.pheme.eu Some Meeting, Some Place, Some Date

Physical Infrastructure and Virtualization

Storage Infrastructure

Processing

Knowledge Base

Stream Processing Batch Processing

Mes

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ng /

Com

ms

Mul

tilin

gual

Dat

a

Data Collection

Rumour Classification Usage Curation

Data Value Chain

IT V

alue

Cha

in

IT Big Data Layer

Veracity and Language Value Chain

System Workflow Orchestration

Mul

tilin

gual

Dat

a S

ocia

l Med

ia

Mul

tilin

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Dat

a

Data Data

SW

LT Processing & Analytics

Raw data Repository

Lang Detection

OntoText GraphDB™

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Dat

a M

ultil

ingu

al D

ata

End

Use

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Phe

me

Das

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Jour

nalis

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Event Detection

NLP Processing

Annotation & Training

Cross-media linking

Cross-lingual analysis

Res

ourc

e M

anag

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PHEME Big Data Architecture for veracity analysis


Application areas

Open-source social intelligence tools for data journalism Involves journalists from SwissInfo.ch, the Guardian,

New York Times, and other media

Improving healthcare What health-related rumours are discussed in patient-

clinician consultations Preventative medical advice, e.g. warn patients not to

trust certain rumours, when researching their disease online


PHEME Dashboard And dynamics Over Time/Location

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vs replies


Journalism Dashboard Prototype

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Acknowledgement

The PHEME research project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement No. 611233.

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This document does not represent the opinion of the European Community, and the European Community is not responsible for any use that might be made of its content

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