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MINDPICS

When a Profile is worth more than a Thousand of Hashtags: Automatic Inference of Personality Traits based on Images Shared in Social Networks

Total Cost €

0

EC-Contrib. €

0

Partnership

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 MINDPICS project word cloud

Explore the words cloud of the MINDPICS project. It provides you a very rough idea of what is the project "MINDPICS" about.

day    photos    publicly    budget    degree    insights    vast    shared    sources    scenes    despite    studies    dollars    analytical    predict    customers    textual    combination    generates    soft    posts    description    exchange    techniques    appearing    visual    tools    texts    repository    marketing    image    networks    machine    political    2015    form    learners    proper    coverage    decision    clothes    modern    customer    public    generation    estimate    communication    million    human    prototype    media    logos    deep    inference    personality    geolocalisation    accompanying    fact    learning    objects    brands    trait    accurately    extracted    hidden    opinions    cultural    images    brand    doubling    understand    uploaded    provides    source    gap    ignored    profiles    daily    billion    validated    revolutionize    monitoring    alone    demands    biometric    near    sociology    discovering    final    pictures    65    people    social    essence    interests    platform    reaching    solely    playing    applies    spectrum    digital    anthropology    sentiments   

Project "MINDPICS" data sheet

The following table provides information about the project.

Coordinator
VISUAL TAGGING SERVICES 

Organization address
address: LG PARC DE LA RECERCA DE LA UAB EDIF EUREKA CERDANYOLA DEL VALLES
city: BARCELONA
postcode: 8193
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Project website http://platform.visual-tagging.com/
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
2. H2020-EU.2.3.1. (Mainstreaming SME support, especially through a dedicated instrument)
 Code Call H2020-SMEINST-1-2016-2017
 Funding Scheme SME-1
 Starting year 2016
 Duration (year-month-day) from 2016-07-01   to  2016-11-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    VISUAL TAGGING SERVICES ES (BARCELONA) coordinator 50˙000.00

Map

 Project objective

The social media, as a major platform for communication and information exchange, provides a rich repository of the opinions and sentiments of 2.3 billion users about a vast spectrum of topics. Such knowledge is playing an important role to understand and predict human decision making, while becoming essential for digital marketing, brand monitoring, and customer understanding, among others. Although social marketing budget is doubling each year, reaching 9 billion dollars in 2015 in US alone, the analysis of trends, topics and brands in social networks is based solely on textual posts. Despite the fact that 65% of users are visual learners, the knowledge embedded in the 1.8 billion photos uploaded daily in public profiles is ignored. Based on this gap in coverage, we propose a platform which applies the most modern machine learning techniques, based on Deep Learning, to understand near 1 million images publicly shared per day, for the inference of relevant insights from social profiles. In essence, this visual knowledge is extracted using our current know-how on image understanding, in the form of a working, validated prototype which generates a description of (i) soft-biometric characteristics of people appearing in shared pictures; (ii) their type of clothes, logos, objects and scenes; and, (iii) when available, its geolocalisation and accompanying texts. Working during this project in a proper combination of these sources of knowledge will enable the final product to estimate more accurately the social user's demands and cultural-driven interests, eventually reaching some degree of personality trait description. Discovering the hidden customers of a given brand, based on the pictures shared in their public profiles, will revolutionize the next generation of analytical tools for social networks monitoring, making the process of images understanding an essential source of information in future marketing, anthropology, sociology, and political studies

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The information about "MINDPICS" are provided by the European Opendata Portal: CORDIS opendata.

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