Instruments and attitudes towards communication technology have changed.
Web 2.0 enables a multi-way information exchange; web 3.0 - semantic web - has yet to come but it is certainly a largely debated matter; location technologies and the 'map revolution' give space a relevant role in the understanding of social phenomena; web and mobile apps are easily produced with consolidated technology and programming standards; Application Programming Interfaces are commonly used to access and analyze the contents of web databases. Smart-phones and tablets integrate all these hardware and software technologies.
Social and web networks, blogs, and others have defined a new perspective on the ways people share personal information. The concepts of privacy and shared knowledge have taken on new meanings and forms.
Having all this in mind, the author has tried to design a future time use survey whose field work is carried out by means of a mobile application for smart-phone, using a well known instant microblogging service - Twitter - and a web service which enables the automatic georeference of the microblog texts. Data could be easily collected in real-time using Twitter Streaming API and be directly available in a machine readable format. Some information would be automatically gathered by the application - e.g. time and space stamp - and therefore the interviewees would concentrate on narrating daily life aspects that be described by them only. A rough test has been conducted so as to verify the practical feasibility of the idea.
Despite the fact that this proposal seems to foster a certain potential in the author's opinion, it is not free from problems and drawbacks. The two major concerns are related to the protection of the confidentiality and the possible bias caused by the digital divide. Furthermore, such a change in the survey instruments and procedures produces a totally new set of sources for non-probabilistic errors which has yet to be dealt with. But, one could say 'what survey doesn't suffer from fieldwork errors?' and keep on working to evaluate them and find out solutions to them.
Moreover, if one considers social networks and microblogging as spontaneous narrations of daily life, these web resources may be also seen as potential databases - to be interrogated using API - to extract time use data in an unconventional form. For instance, sleep-wake cycle could be studied by analyzing the timing and some content specific tweets. But this is another story.