Investigating the value of privacy on online social networks: conjoint analysis

Popularity of Online Social Networks has been recently overshadowed by the privacy problems they pose. Users are getting increasingly vigilant concerning information they disclose and are strongly opposing the use of their information for commercial purposes. Nevertheless, as long as the network is offered to users for free, providers have little choice but to generate revenue through personalized advertising to remain financially viable. Our study empirically investigates the ways out of this deadlock. Using conjoint analysis we find that privacy is indeed important for users. We identify three groups of users with different utility patterns: Unconcerned Socializers, Control-conscious Socializers and Privacy-concerned. Our results provide relevant insights into how network providers can capitalize on different user preferences by specifically addressing the needs of distinct groups in the form of various premium accounts. Overall, our study is the first attempt to assess the value of privacy in monetary terms in this context.

Privacy concerns and identity in online social networks

Driven by privacy-related fears, users of Online Social Networks may start to reduce their network activities. This trend can have a negative impact on network sustainability and its business value. Nevertheless, very little is understood about the privacy-related concerns of users and the impact of those concerns on identity performance. To close this gap, we take a systematic view of user privacy concerns on such platforms. Based on insights from focus groups and an empirical study with 210 subjects, we find that (i) Organizational Threats and (ii) Social Threats stemming from the user environment constitute two underlying dimensions of the construct “Privacy Concerns in Online Social Networks”. Using a Structural Equation Model, we examine the impact of the identified dimensions of concern on the Amount, Honesty, and Conscious Control of individual self-disclosure on these sites. We find that users tend to reduce the Amount of information disclosed as a response to their concerns regarding Organizational Threats. Additionally, users become more conscious about the information they reveal as a result of Social Threats. Network providers may want to develop specific mechanisms to alleviate identified user concerns and thereby ensure network sustainability.

Detecting Functional Hubs of Ictogenic Networks

Quantitative EEG (qEEG) has modified our understanding of epileptic seizures, shifting our view from the traditionally accepted hyper-synchrony paradigm toward more complex models based on re-organization of functional networks. However, qEEG measurements are so far rarely considered during the clinical decision-making process. To better understand the dynamics of intracranial EEG signals, we examine a functional network derived from the quantification of information flow between intracranial EEG signals. Using transfer entropy, we analyzed 198 seizures from 27 patients undergoing pre-surgical evaluation for pharmaco-resistant epilepsy. During each seizure we considered for each network the in-, out- and total "hubs", defined respectively as the time and the EEG channels with the maximal incoming, outgoing or total (bidirectional) information flow. In the majority of cases we found that the hubs occur around the middle of seizures, and interestingly not at the beginning or end, where the most dramatic EEG signal changes are found by visual inspection. For the patients who then underwent surgery, good postoperative clinical outcome was on average associated with a higher percentage of out- or total-hubs located in the resected area (for out-hubs p = 0.01, for total-hubs p = 0.04). The location of in-hubs showed no clear predictive value. We conclude that the study of functional networks based on qEEG measurements may help to identify brain areas that are critical for seizure generation and are thus potential targets for focused therapeutic interventions.

Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

Epileptic networks are strongly connected with and without the effects of interictal discharges

OBJECTIVE Epilepsy is increasingly considered as the dysfunction of a pathologic neuronal network (epileptic network) rather than a single focal source. We aimed to assess the interactions between the regions that comprise the epileptic network and to investigate their dependence on the occurrence of interictal epileptiform discharges (IEDs). METHODS We analyzed resting state simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) recordings in 10 patients with drug-resistant focal epilepsy with multifocal IED-related blood oxygen level-dependent (BOLD) responses and a maximum t-value in the IED field. We computed functional connectivity (FC) maps of the epileptic network using two types of seed: (1) a 10-mm diameter sphere centered in the global maximum of IED-related BOLD map, and (2) the independent component with highest correlation to the IED-related BOLD map, named epileptic component. For both approaches, we compared FC maps before and after regressing out the effect of IEDs in terms of maximum and mean t-values and percentage of map overlap. RESULTS Maximum and mean FC maps t-values were significantly lower after regressing out IEDs at the group level (p < 0.01). Overlap extent was 85% ± 12% and 87% ± 12% when the seed was the 10-mm diameter sphere and the epileptic component, respectively. SIGNIFICANCE Regions involved in a specific epileptic network show coherent BOLD fluctuations independent of scalp EEG IEDs. FC topography and strength is largely preserved by removing the IED effect. This could represent a signature of a sustained pathologic network with contribution from epileptic activity invisible to the scalp EEG.

Legal Framework for Cross-Regional Networks: The Case of Services and Migration

Paper prepared by Marion Panizzon and Charlotte Sieber-Gasser for the International Conference on the Political Economy of Liberalising Trade in Services, Hebrew University of Jerusalem, 14-15 June 2010 Recent literature has shed light on the economic potential of cross-border networks. These networks, consisting of expatriates and their acquaintances from abroad and at home, provide the basis for the creation of cross-border value added chains and therewith the means for turning brain drain into brain circulation. Both aspects are potentially valuable for economic growth in the developing world. Unilateral co-development policies operating through co-funding of expatriate business ventures, but also bilateral agreements liberalising circular migration for a limited set of per-sons testify to the increasing awareness of governments about the potential, which expatriate networks hold for economic growth in developing countries. Whereas such punctual efforts are valuable, viewed from a long term perspective, these top-down, government mandated Diaspora stimulation programs, will not replace, this paper argues, the market-driven liberalisation of infrastructure and other services in developing countries. Nor will they carry, in the case of circular labour migration, the political momentum to liberalise labour market admission for those non-nationals, who will eventually emerge as the future transnational entrepreneurs. It will take a combination of mode 4 and infrastructure services openings-cum regulation for countries at both sides of the spectrum to provide the basis and precondition for transnational business and entrepreneurial networks to emerge and translate into cross-border, value added production chains. Two key issues are of particular relevance in this context: (i) the services sector, especially in infrastructure, tends to suffer from inefficiencies, particularly in developing countries, and (ii) labour migration, a highly complex issue, still faces disproportionately rigid barriers despite well-documented global welfare gains. Both are hindrances for emerging markets to fully take advantage of the potential of these cross-border networks. Adapting the legal framework for enhancing the regulatory and institutional frameworks for services trade, especially in infrastructure services sectors (ISS) and labour migration could provide the incentives necessary for brain circulation and strengthen cross-border value added chains by lowering transaction costs. This paper analyses the shortfalls of the global legal framework – the shallow status quo of GATS commitments in ISS and mode 4 particular – in relation to stimulating brain circulation and the creation of cross-border value added chains in emerging markets. It highlights the necessity of adapting the legal framework, both on the global and the regional level, to stimulate broader and wider market access in the four key ISS sectors (telecommunications, transport, professional and financial services) in developing countries, as domestic supply capacity, global competitiveness and economic diversification in ISS sectors are necessary for mobilising expatriate re-turns, both physical and virtual. The paper argues that industrialised, labour receiving countries need to offer mode 4 market access to wider categories of persons, especially to students, graduate trainees and young professionals from abroad. Further-more, free trade in semi-finished products and mode 4 market access are crucial for the creation of cross-border value added chains across the developing world. Finally, the paper discusses on the basis of a case study on Jordan why the key features of trade agreements, which promote circular migration and the creation of cross-border value added chains, consist of trade liberalisation in services and liberal migration policies.