Davide Gazzè

ABCD SW: autistic behavior & computer-based didactic software

In this demo we show an open source software (SW) program designed to facilitate the execution of Applied Behavior Analysis (ABA) intervention with low-functioning autistic children. The SW is based on Augmentative and Alternative Communication (AAC) and Discrete Trial Training (DTT). The SW automatically records data extractable from the session (times, success/error, etc.), while the tutor inserts subjective data such as type and level of prompt provided to a child, along with comments. The SW adapts the trial to the childs abilities (receptive/verbal) to make it accessible (comprehensible and operable). To offer the child a simple and accessible interaction environment, the tutor and child user interfaces are kept separate and offered on mobile devices. Using a laptop, the tutor sets the exercise that appears on the childs tablet. Synchronization between devices offers the tutor a real-time summary of actions performed by child, freeing up his/her cognitive resources needed to memorize this information and possibly favoring the decision-making process for the ABA intervention.

CAPER: crawling and analysing Facebook for intelligence purposes

Organised crime uses information technology systems to communicate, work or expand its influence. The EU FP7 Security Research Project CAPER (Collaborative information, Acquisition, Processing, Exploitation and Reporting for the prevention of organised crime), created in cooperation with European Law Enforcement Agencies (LEAs), aims to build a common collaborative and information sharing platform for the detection and prevention of organised crime, which exploits Open Source Intelligence (OSINT). LEAs are becoming more inclined to using OSINT tools, and particularly tools able to manage Online Social Networks (OSNs) data. This paper presents the CAPER Facebook crawling and analysis subsystem. Heuristic algorithms have been implemented in order to extract specific properties of Facebooks social graph, in particular user interactions. To support analysis tasks specifically, extensive effort has been spent on the analysis of textual user generated content and on the recognition of named-entities, in particular person names, locations and organisations. Relationships between users and entities mentioned in posts and in related comments are created and merged into the users networks extracted from the social graph. All entity relationships are finally visualised in user-friendly network graphs.

Facebook: a new tool for collecting health data?

This study investigates the use of social networks as a scientific tool for gathering medical data from young subjects while promoting healthier habits. Our first hypothesis is that social networks can facilitate epidemiological studies, reducing time and cost. The second question is whether social networks can enable the collection of data from young and healthy subjects who are otherwise beyond the reach of conventional social health polls. A Facebook application was created to collect data concerning adherence to the Mediterranean diet, considering the significant risk of cardiovascular and neurological degenerative diseases in subjects with poor adherence to a healthy diet. More than 1400 users were recruited in a short time without any promotional action. Collected data indicate that adherence to the Mediterranean diet is in general greater in older users vs young (p <0.01) and Italian vs Other Countries (mainly participants from the US) (p <0.03), while no statistical differences were found concerning gender. Results show that the proposed approach offers advantages in terms of reduced cost, faster data gathering and processing, and improved efficiency compared to a form-based epidemiology campaign. However, the initial network may influence the sample constitution in age and geographical location, especially if the spread does not become viral and autonomous. Based on the case study, we provide designers of Facebook apps with some simple guideline suggestions aimed at maximizing the heterogeneity of the sample, in order to collect significant data. The proposed scenario, suitable for collecting health data, can easily be extended to other fields.

SocialTrends: A Web Application for Monitoring and Visualizing Users in Social Media

Nowadays social media trends are becoming very important to describe the variation of popularity, activity and influence of an entity. In this paper we define an abstract model which can be used on different social media to compare metrics with the same meaning. In particular we describe three classes of metrics: popularity, activity and influence. We also present SocialTrends, a web application (http://www.social-trends.it/) which collects, elaborates and visualizes social media data. Finally, we describe one experiment we have done to test SocialTrends.

WorkMail: Collaborative Document Workflow Management by Email

Processing documents is a critical and crucial aspect for enterprises. The management of documents involves several people and can be a long and time-wasting process. We developed a document workflow engine based on email paradigm. Exploiting a web application, the subject of the workflow, the document, can be sent as an email attachment. Our solution overcomes the current limitation in the use of Document Workflow software, especially regarding user experience. With our system there is no need for users to learn how a new framework works. In addition, users with different roles have different customized view of the document. Moreover a suggest feature has been implemented; the system suggests a possible receiver for the document, depending on the document flow.

Integration of External Data in Document Workflows via Web Services

In recent years the adoption of systems to automatically manage information assets in networked, collaborative ways has become vital for enterprises. In this work we focus on collaborative document management systems, where actual document development relies on accessing structured data in remote repositories. Forms within documents must be filled in with proper data items: An automated support to gather the required remote data may substantially improve the overall document management process. The Web Service technology is of fundamental help in this setting, because it lets remote data be exposed to potential clients according to standard interfaces. On the other hand, document management systems must be modified to provide this new kind of data access. This paper introduces a novel approach to support remote data integration in documents handled by Content Management Systems. According to the reported experience, such a data integration can be regarded as an enabling feature for a better exploitation of document workflow systems.

Towards a General Architecture for Social Media Data Capture from a Multi-Domain Perspective

Online Social Media (OSM) platforms, such as Facebook or Twitter, are part of everyday life as powerful communication tools. They let users communicate anywhere anytime, and improve their own public image. For this reason, OSM are becoming more and more popular. Social Media data may play a crucial role in various decision-making processes. In this setting, research topics connected to monitoring of Social Media data are becoming increasingly important. The presented work is grounded on direct extensive experiences in data collection from different Social Media sources, and on the different methodologies applied in different reference domains (namely Online Reputation, Social Media Intelligence, and Opinion Mining in tourism). The crawlers developed for these domains provide valuable suggestions to elicit diverse requirements. After lessons learned in such fields, a general architecture for data capture from Social Media sources has been devised, and the interfaces of the composing modules have been defined. The resulting API can be exploited for an orderly re-engineering of crawling tools in the reference domains, thus implementing specific versions of the generic architecture.

An overview of the tourpedia linked dataset with a focus on relations discovery among places

Tourpedia (http://tour-pedia.org) is an open initiative which contains a linked dataset of tourism places, i.e. accommodations, attractions, points of interest (POIs) and restaurants. Tourpedia extracts and integrates information about places from four different social social media: Facebook, Foursquare, Google Places and Booking.com. The resulting knowledge base currently consists of more than 6M RDF triples and describes almost 500.000 places, each of which is identified by a globally unique identifier, which can be dereferenced over the Web into a RDF description. This paper gives an overview of the Tourpedia knowledge base and illustrates how new relations are discovered among places through Named Entity Recognition (NER) tools.