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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.

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

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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