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 €
0EC-Contrib. €
0Partnership
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0MINDPICS 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.
Project "MINDPICS" data sheet
The following table provides information about the project.
| Coordinator |
VISUAL TAGGING SERVICES
Organization address contact info |
| 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.
| # | ||||
|---|---|---|---|---|
| 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.