Do adverts increase the probability of finding online cognitive behavioural therapy for depression? Cross-sectional study

Objective To estimate the effect of online adverts on the probability of finding online cognitive behavioural therapy (CBT) for depression. Design Exploratory online cross-sectional study of search experience of people in the UK with depression in 2011. (1) The authors identified the search terms over 6 months entered by users who subsequently clicked on the advert for online help for depression. (2) A panel of volunteers across the UK recorded websites presented by normal Google search for the term ‘depression’. (iii) The authors examined these websites to estimate probabilities of knowledgeable and naive internet users finding online CBT and the improved probability by addition of a Google advert. Participants (1) 3868 internet users entering search terms related to depression into Google. (2) Panel, recruited online, of 12 UK participants with an interest in depression. Main outcome measures Probability of finding online CBT for depression with/without an advert. Results The 3868 users entered 1748 different search terms but the single keyword ‘depression’ resulted in two-thirds of the presentations of, and over half the ‘clicks’ on, the advert. In total, 14 different websites were presented to our panel in the first page of Google results for ‘depression’. Four of the 14 websites had links enabling access to online CBT in three clicks for knowledgeable users. Extending this approach to the 10 most frequent search terms, the authors estimated probabilities of finding online CBT as 0.29 for knowledgeable users and 0.006 for naive users, making it unlikely CBT would be found. Adding adverts that linked directly to online CBT increased the probabilities to 0.31 (knowledgeable) and 0.02 (naive). Conclusions In this case, online CBT was not easy to find and online adverts substantially increased the chance for naive users. Others could use this approach to explore additional impact before committing to long-term Google AdWords advertising budgets

Social search : application, possibilities and challenges

Razvoj društvenih medija i weba 2.0. omogućio je iskorištavanje društveno stvorenog sadržaja kako bi se poboljšali rezultati pretraživanja. U radu se prikazuju mogućnosti primjene društvenog pretraživanja, njegove prednosti i nedostaci. Cilj je pokušati odgovoriti na pitanje da li se društveno pretraživanje može uspješno koristiti kao nadopuna tradicionalnom pretraživanju. Tradicionalno pretraživanje često ostavlja korisnike nezadovoljnima jer nisu uspjeli pronaći odgovor na svoju informacijsku potrebu. Nekada se to događa zbog samih korisnika koji ne znaju pravilno oblikovati svoju potrebu u upit, a nekada zbog toga što pretraživači zanemaruju kontekst pretraživanja i specifične potrebe pojedinog korisnika. Društveno pretraživanje pokušava razriješiti oba navedena problema. U prvom je dijelu rada opisan pojam pretraživanja informacija i objašnjen način na kojem funkcionira tradicionalno pretraživanje. Navedene su vrste modela pretraživanja, korisničkih upita i podjela korisnika prema stručnosti pretraživanja, te su analizirani utjecaji koje je razvoj World Wide Weba imao na pretraživanje informacija. U drugom dijelu rada prikazane su različite primjene društvenog pretraživanja, a kroz primjere objašnjen je način njihovog funkcioniranja i arhitektura sustava.Social Media and development of Web 2.0. made it possible to make use of sociallygenerated content to improve search results. The paper presents the possibilities of social search, its advantages and disadvantages. The goal is to try to answer whether social search can be successfully used to complement traditional search. Traditional search often leaves users dissatisfied because they have been unable to find an answer to their information need. Sometimes this happens because the users do not know how to properly convey their need into query, and sometimes because search engines ignore the search context and specific needs of the individual user. Social search is trying to solve both of these problems. The first part of the paper describes the concept of information retrieval and explains how traditional search works. Types of search models, user queries, and user taxonomy are listed, and the impacts that the development of the World Wide Web has had on information retrieval have been analyzed. In the second part of the paper, various applications of social search are presented, and through the examples system architecture and the way they function is explained

Utilização de técnicas de recomendação para suportar processos de negociação Conceptual

Dissertação de Mestrado em Engenharia InformáticaA construção de uma conceptualização partilhada requer a colaboração entre todos aqueles que dela tirarão partido no futuro. Tendo isso em conta, é necessário envolver os participantes num processo de negociação com vista a obter acordos mais rápidos no que diz respeito aos resultados da conceptualização, como sendo especificações de alto nível para um dado domínio ß. Para suportar e melhorar tal processo, o presente documento tem como finalidade a apresentação da abordagem RecommendME, uma extensão do método ColBlend. Esta abordagem tem como inspiração alguns princípios e caraterísticas encontrados nos sistemas de recomendação, que, na nossa opinião, serão uma mais valia para o processo de construção de uma conceptualização partilhada, no sentido de que irão apoiar a rede colaborativa na tarefa de a desenhar, tornando-a uma conceptualização de alto nível do domínio que se pretende representar.The construction of a shared conceptualization requires collaboration between all those who will use it in the future. Thus, it is necessary to engage the participants in a negotiation process in order to reach better and faster agreements about the main conceptualization outcomes, as high-level specifications of a given domain ß. To support and improve such process, the current document presents the RecommendME approach, an extension of the ColBlend method. This approach takes advantage of some of the features found in recommender systems, which, in our opinion, will aid a collaborative network at the task of designing a high-level conceptualization of a specific domain

Policy Implications of User-Generated Data Network Effects

User-generated data (UGD) network effects are an exciting and novel economic force. They upset conventional market competition dynamics, and they lead to the formation of dominant data platforms with market power that spans different and seemingly unrelated markets. This article explains that UGD network effects are a blessing and a curse. They provide dominant data platforms with the opportunity to generate welfare-enhancing efficiencies as well as welfare-reducing anticompetitive harms. After exploring the economic opportunities and social threats, this article explores the implications of UGD network effects on competition policy. Drawing on traditional network effects theory, this article proposes and critically examines a host of remedial approaches for policymakers to consider. These remedies include modernized public utility-style regulation, open access policies, and adjusted standards for anti-monopolization and merger scrutiny

User-Generated Data Network Effects and Market Competition Dynamics

This Article defines User-Generated Data (“UGD”) network effects, distinguishes them from the more familiar concept of traditional network effects, and explores their implications for market competition dynamics. It explains that UGD network effects produce various efficiencies for digital service providers (“data platforms”) by empowering their services’ optimization, personalization, and continuous diversification. In light of these efficiencies, competition dynamics in UGD-driven markets tend to be unstable and lead to the formation of dominant multi-industry conglomerates. These processes will enhance social welfare because they are natural and efficient. Conversely, countervailing UGD network effects also empower data platforms to detect and neutralize competitive threats, price discriminate among users, and manipulate users’ behaviors. The realization of these effects will result in inefficiencies, which will undermine social welfare. After a comprehensive analysis of conflicting economic forces, this Article sets the ground for informed policymaking. It suggests that emerging calls to aggravate antitrust enforcement and to “break up” Big Tech are ill-advised. Instead, this Article calls for policymakers to draw inspiration from traditional network industries’ public utility and open-access regulations

User behavior in microblogs with a cultural emphasis

The main objective of this thesis is to carry out a multidisciplinary study of the behavior of microblog users. To that end we first explore several user behavior patterns employing data mining techniques. Then we use social science theories of culture and socio-economic indicators to better understand differences and similarities of user behavior across countries. We found several insights on user behavior such as (i) social link recommendations made by current friends have a large effect on link formation and the accepted recommendations have more longevity than other links; (ii) as users mature, they evolve to adopt microblogs as a news media rather than a social network; (iii) the collective behavior of users from some countries standout, based on certain special characteristics such as conversations, reciprocity, etc.; (iv) national culture determines the temporal patterns with which users post, or the extent to which they mention, follow, recommend and befriend others; and (v) socio-economic and cultural features improve the prediction of communication strength among users from different countries.El objetivo principal de esta tesis es realizar un estudio multidisciplinario sobre la conducta de los usuarios en microblogs. Para ello primero exploramos varios patrones de comportamiento de usuario usando técnicas de minería de datos. Luego usamos algunas teorías de las ciencias sociales en cultura e indicadores socioeconómicos para comprender mejor las diferencias y similitudes del comportamiento de los usuarios en diferentes países. Encontramos varios resultados interesantes sobre el comportamiento del usuario, tales como, (i) las recomendaciones de enlaces sociales hechas por amigos tienen un gran efecto sobre la formación de enlaces sociales y las recomendaciones aceptadas tienen más longevidad que otros enlaces; (ii) a medida que los usuarios maduran, estos evolucionan a usar los microblogs como un medio de comunicación en lugar de una red social; (iii) el comportamiento colectivo de los usuarios de algunos países se destaca en base a ciertas características peculiares, tales como conversaciones, reciprocidad, etc.; (iv) la cultura nacional determina los patrones temporales con los que los usuarios publican mensajes, o el grado en que se mencionan, recomiendan y siguen los unos a los otros; y (v) las características socioeconómicas y culturales ayudan a mejorar la predicción de la intensidad de la comunicación entre los usuarios de diferentes países