This thesis addresses the unclear and puzzling responsibility of both traditional media and political actors for the lack of substantial political issues in the news coverage of political elections. The literature has observed a growing tendency of journalists, when reporting elections, to emphasize aspects such as strategy/horse-race and conflict, instead of presenting relevant policy information. This study analyzes to what extent a media logic is hindering the electoral competitors from producing more informative and less conflict-driven campaigns, by examining the media frames employed by journalists, in their newspaper articles, and by the main parties/candidates, in their social media campaigns. Different to other communication channels, social media offer politicians and parties a unique opportunity to bypass journalists and directly present their messages to a larger and more diverse audience. The main objective of this study is to understand if political elections are framed differently by journalists and political actors and test two sets of competing hypotheses: Uninformative News (if journalists distort political events to become more attractive rather than informative) and Hollow Campaigns (if the politicians themselves avoid discussing issues in their campaigns). In order to so, an extensive content analysis of the press and social media was carried out for four first-order elections (US 2012, Italy 2013, Brazil 2014 and Portugal 2015). For each election, two newspapers and the campaigns of the main parties/candidates on three social media (Facebook, Twitter and YouTube) were manually coded during the four weeks before election day. The results show that the press was consistently more likely than social media to deal with aspects such as strategy/horse-race and conflict. In addition to this, the salience of substantive political issues was also higher in social media campaigns than in newspaper articles. Overall, despite some differences between candidates/parties, countries and social media platforms, the results consistently give support to the Uninformative News hypothesis.