Analizing user generated content for social science
Il Lab20, cioè Io, Luca, Fabio, Chiara e Stefano abbiamo scritto insieme l'abstract del nostro primo articolo scritto a cinque mani, vi giro parte del testo, che ne pensate?
Abstract
During the last few years the Internet has been increasingly used by people as a read-write medium. Thanks to the dropped prices and skills necessary to afford and use technologies aimed to create digital contents, a large amount of people in the world is now able to produce persistent digital information.
The online network of communications is persistent, searchable, replicable and addressed to an invisible audience. Due to these properties online conversations may be analyzed with standard content analysis qualitative or quantitative techniques.
The aim of this paper is to show how this large amount of data might be used for sociological research. In particular, the paper will present either an example of research or a technological approach.
Youtube.com is arguably the most popular site for people who are eager to share video across the Internet and it is the largest of all video sharing websites. In order to understand new visual cultures of pregnancy and birth, one cannot fail to consider the impressive number of videos tagged with the words “pregnancy”, “birth” and “ultrasounds”. We aim at analyzing this contemporary phenomenon both by examining many videos, and by emphasizing the shift from birth as a private experience to parturition as a “networked event” potentially shared with anyone.
One important aspect of this paper is the technological approach towards the realization of a software platform to retrieve information via web. This solution allows social scientists to manage data model, fruition and analysis using a new technology application service based.
The system we will present, manage data in RSS format, retrieve information by consume service brokers provided by major web 2.0. In addiction, our system allows indexing and search operation to allow end user to query optimize their tag classification and/or retrieve pertinent data transforming information by a graphical engine directly on the web.