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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.

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

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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