Abstract

The emergence of Twitter appears to be changing information practices. Hence, a great deal of recent research is based on its popularity among communicators, reaching the conclusion that it serves to increase interactivity with readers. But to what degree is it true that it contributes to a type of journalism which is more open to the public? This research aims especially to clarify two main questions: what specific uses do journalists make of Twitter and to what extent does twoway interaction with the public take place through this medium? It is based on the quantitative analysis of a sample comprising almost 5 million tweets posted by 1,504 Spanish media communicators, perhaps the largest sample studied so far. The analysis shows the existence of a twospeed Twitter (with a minority of influential communicators and a majority who have little impact), which has negligible interaction with followers. With few exceptions, the communicators establish endogamous relationships on Twitter. They respond to mention and retweet colleagues, failing to take advantage of the multidirectional potential offered by the platform. This research expands the empirical basis which can be used to consider and discuss the scope and limits of user participation in information events. Many authors have theorized on this subject, perhaps too enthusiastically and arguably from a somewhat utopian perspective.

Abstract

The concept of microblogging is described. Some of the main tools there are (Twitter, Jaiku, Pownce, Jisko, etc.) and how they work. Then the concept of liveblogging is introduced, and its possibilities related to video and audio. Finally, it offers some ideas to implement these tools in the information units.

Abstract

The Umap project is a practical attempt to obtain collective intelligence from the flow of social networks: links that users share are analyzed, filtered and rated, making it feasible to convert collective intelligence into structured information. For example, information, comments and links that are shared by users belonging to a certain community –e. g., linguistic, social, thematic, organizational- are analyzed in real time to obtain trends at specified intervals (e. g., hourly, daily, weekly...). By means of simplicity search algorithms, the information flow becomes an automated news bulletin with its own value but to which opinions and the relevance that users of social networks give them are added. Umap opens the way for future applications centred in the extraction of information and collective intelligence from communities that share social, political, economical, trading, business, products, brand, technological and other interests through social networks. The first applications of the Umap project developed by CodeSyntax are already available at http://www.umap.eu

Abstract

This article examines President Donald Trump’s treatment on Twitter towards the US media during his first six months in office, from January 20 to July 20, 2017. Based on a content analysis of the tweets published in the account @realDonaldTrump, we study the mentions to the media and their tone, and the presence and use of keywords related to the media. In addition, we analyze Trump’s treatment of the press in relation to political control and the role of journalism as watchdog of democracy. As main conclusions it is noted that Trump, in a very simplistic way, praises those media that treat him positively and criticizes those that –in his view- portrait him negatively, which are often dubbed as fake news. Through this process, Trump avoids the mediator role of the media and rejects the watchdog role that democratic systems have attributed to them.