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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 €

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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.

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

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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