Opendata, web and dolomites

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

0

Views

0

 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.

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

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

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "MINDPICS" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.2.1.1.;H2020-EU.2.3.1.)

Assist (2015)

Telocate ASSIST – Development and marketing of an acoustic solution for localization and navigation of people in buildings using the smartphone

Read More  

Leaf Line (2018)

The First Global Ground Station Network to Fully Exploit Microsatellites Data

Read More  

Enterprise BIM (2017)

Enterprise BIM digitization platform feasibility verification

Read More