The legalisation of online gambling in multiple territories has caused a growth in the exposure of consumers to online sports betting (OSB) advertising. While some efforts have been made to understand the visible structure of betting promotional messages, little is known about the latent components of OSB advertisements. The present study sought to address this issue by examining the metaphorical conceptualisation of OSB advertising. A sample of Spanish and British television OSB advertisements from 2014 to 2016 was analysed (N = 133). Following Lakoff and Johnson’s conceptual metaphor theory, four main structural metaphors that shaped how OSB advertising can be understood were identified: betting as (1) an act of love, (2) a market, (3) a sport, and (4) a natural environment. In general, these metaphors, which were found widely across 29 different betting brands, facilitated the perception of bettors as active players, with an executive role in the sport events bet upon, and greater control over bet outcomes.

The pervasiveness of sports betting marketing and advertising is arguably normalising betting behaviour among increasingly larger groups of population. In their adverts, bookmakers represent characters and situations that conventionalise betting and promote specific behaviours while ignoring others. The present study examined a sample of British and Spanish sports betting television adverts (N=135) from 2014 to 2016 to understand how bettors and betting are being represented. Using content analysis, 31 different variables grouped into seven broad categories were assessed, including general information about the advert, the characters and situations represented, the identification of the characters with sports, the use of online betting, the co-representation of gambling along other risky behaviours such as eating junk food and drinking alcohol, the amount of money wagered, and other variables such as the representation of free bets, humour, and celebrities. The results showed a male-dominant betting representation with no interaction between women. Typically, bettors were depicted surrounded by people but isolated in their betting, emphasizing the individual consumption practice that mobile betting promotes. In-play betting was observed in almost half of the adverts. A little empirical evidence indicates that betting while watching sport in betting adverts is associated with emotionally charged situations such as celebrations and/or alcohol drinking. Bettors were typically depicted staking small amounts of money with large potential returns, implying high risk bets. Overall, the study provides preliminary evidence in understanding the social representation of betting behaviour by bookmakers and critiques the problematic consequences of such representation from a public health perspective.

Twitter has become a privileged data source for analyzing the behavior of users when interacting online. This research aims to explore the interactive behavior of users in political discussions and the changes in their behavior over time. Understanding the interactive functions of Twitter (retweeting, mentioning, and replying) as digital traces of users’ behavior, we analyze the patterns of interaction of politicians, media, and citizens in two political discussions in Spain during the 2015 and 2016 general elections. Our results confirm previous studies that prove the homophilic behavior of politicians and citizens in political discussions. The networks of interaction, in particular, the retweet network, resemble echo chambers. It also shows that media play the role of weak ties of the networks. The analysis also shows that the patterns of interaction remained stable after the repetition of the election, and only a meager part of the users participating in both discussions changed their behavior. This article aims to contribute to the use of Twitter as a source for understanding people’s interactions is political discussions in social media and their dynamics across time.

(UPF), teaches in the Departments of Journalism and Advertising. He is director of the master's degree in Digital Documentation (UPF) and the master's degree in Search Engines (UPF). He has a degree in Educational Sciences, as well as in Library and Information Science. He is an engineer in Computer Science and has a master's degree in Free Software. He is conducting research in web positioning (SEO), usability, search engine marketing and conceptual maps with eyetracking techniques.

Search engine optimization (SEO) constitutes the set of methods designed to increase the visibility of, and the number of visits to, a web page by means of its ranking on the search engine results pages. Recently, SEO has also been applied to academic databases and search engines, in a trend that is in constant growth. This new approach, known as academic SEO (ASEO), has generated a field of study with considerable future growth potential due to the impact of open science. The study reported here forms part of this new field of analysis. The ranking of results is a key aspect in any information system since it determines the way in which these results are presented to the user. The aim of this study is to analyze and compare the relevance ranking algorithms employed by various academic platforms to identify the importance of citations received in their algorithms. Specifically, we analyze two search engines and two bibliographic databases: Google Scholar and Microsoft Academic, on the one hand, and Web of Science and Scopus, on the other. A reverse engineering methodology is employed based on the statistical analysis of Spearman’s correlation coefficients. The results indicate that the ranking algorithms used by Google Scholar and Microsoft are the two that are most heavily influenced by citations received. Indeed, citation counts are clearly the main SEO factor in these academic search engines. An unexpected finding is that, at certain points in time, Web of Science (WoS) used citations received as a key ranking factor, despite the fact that WoS support documents claim this factor does not intervene.

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Background: Support groups play an important role in diabetes understanding and education. This study aims to find connections between participating in diabetes-related online communities (groups and forums) and the self-reported degree of self-care management and health problems associated with type 1 and 2 diabetes. Methods: A cross-sectional study using an online survey was conducted and 307 participants were recruited. Participants were asked about diabetes self-care management (glucose management, healthcare, dietary restrictions, and physical activity) and complications related to the disease, as well as their participation in online social groups and forums (duration, time, and intensity). Results: Belonging to diabetes-related online support groups (OSGs) was associated with lower scores in healthcare and self-management of diabetes ( M = 2.98, SD = 1.07, n = 207, for belonging to OSGs; and M = 4.22, SD = 0.59, n = 97, for not belonging to OSGs). These differences were not statistically significant for type 1 diabetes individuals ( M = 4.33, SD = 0.47, n = 28, for belonging to OSGs, and M = 4.29, SD = 0.48, n = 52, for not belonging to OSGs), but were highly significant for type 2 diabetes (T2D) individuals ( M = 2.41, SD = 0.68, n = 144, for belonging to OSGs; and M = 4.14, SD = 0.64, n = 61, for not belonging to OSGs). People with both type 1 and 2 diabetes reported to have suffered more complications derived from diabetes when they belonged to an OSG, but greater statistically significant differences were found in type 2 individuals. Conclusion: Patients with T2D who participate in OSGs show a higher correlation with having lower levels of diabetes self-care management as well as health complications related to the disease.

The Retweet Overlap Network (RON) method has proved to be successful in quantifying the distances between political parties in multiparty democracies (Guerrero-Solé, Corominas-Murtra & López-González, 2014; Guerrero-Solé, 2017). These distances are frequently used in political science to explain the formation of coalitions and governments (Volden & Carrubba, 2004). This paper aims to explore how the data collected from Twitter can be related to the ideological similarities between political parties drawing on an extended development of the RON method that calculates the overlaps between the communities of retweeters of the most influential users in a political discussion. The method is applied to two conversations in Twitter during the last two General Elections in Spain in 2015 and 2016. Our results are consistent with the dynamics and the outcomes of the bargaining processes after both elections, and support Spanish President's statement on the reasonableness of a government of the Popular Party (PP), the Spanish Socialist Workers' Party (PSOE) and the Citizens-Party of the Citizenry (Cs) (Del Riego, 2016) after the Spanish General Elections in 2016. 2 This work links quantitative analysis of the overlaps of the parties' communities of retweeters with the theories of coalition and government formation. It aims to be a contribution to the exploration of Twitter metrics that can be used as new indicators of the support for coalitions in multiparty democracies.