Facebook-сторінки латвійських порталів новин: ефективність використання функціоналу

Facebook has long considered media as partners, and therefore creates various tools to work with their audience. In turn, media companies and content providers use Facebook not only to increase traffic, but also to better understand their users. This study compares web pages of the three leading Latvian news portals (Delfi.lv, Apollo.lv and TVNET.lv) in order to study the effectiveness of using all the features provided by functionality of a social network. Applying conversionary analysis to build a typical communicative model and taking into consideration characteristic features of social network, it is established that the type of content significantly affects the user’s actions. It is revealed that the functionality of social network has characteristic features, among which is communication and entertainment component, as well as socialization and self-presentation. In order to obtain quantitative indicators necessary for modeling, we have used web service of content analytics of social networks: ER, LR, TR metrics are used to analyze dive depth, visit frequency and Facebook page mapping. The obtained results indicate a low level of user behavior on the pages of the examined portals in Facebook. The uniform distribution of attention of visitors between photos, text and hyperlinks does not allow to identify priority formats. It has been established that Facebook pages of online news resources are likely to be nonpriority media activity, the task of which is to ensure the presence of resources in the system of social media and increase intensity of information exchange. The study shows that there is no systematic work on integrated representation of Latvian news portals Delfi, TVNet and Apollo on Facebook. Editorial offices do not adapt publications to the specifics of the social network without formatting content, but mainly promote links that lead to the official media portal. The general lack of hashtags system indicates minimal optimization of editorial content for the social network Facebook