Privacy and the City:user identification and location semantics in location-based social networks

With the advent of GPS enabled smartphones, an increasing number of users is actively sharing their location through a variety of applications and services. Along with the continuing growth of Location-Based Social Networks (LBSNs), security experts have increasingly warned the public of the dangers of exposing sensitive information such as personal location data. Most importantly, in addition to the geographical coordinates of the user’s location, LBSNs allow easy access to an additional set of characteristics of that location, such as the venue type or popularity. In this paper, we investigate the role of location semantics in the identification of LBSN users. We simulate a scenario in which the attacker’s goal is to reveal the identity of a set of LBSN users by observing their check-in activity. We then propose to answer the following question: what are the types of venues that a malicious user has to monitor to maximize the probability of success? Conversely, when should a user decide whether to make his/her check-in to a location public or not? We perform our study on more than 1 million check-ins distributed over 17 urban regions of the United States. Our analysis shows that different types of venues display different discriminative power in terms of user identity, with most of the venues in the “Residence” category providing the highest re-identification success across the urban regions. Interestingly, we also find that users with a high entropy of their check-ins distribution are not necessarily the hardest to identify, suggesting that it is the collective behaviour of the users’ population that determines the complexity of the identification task, rather than the individual behaviour.

It's the way you check-in:identifying users in location-based social networks

In recent years, the rapid spread of smartphones has led to the increasing popularity of Location-Based Social Networks (LBSNs). Although a number of research studies and articles in the press have shown the dangers of exposing personal location data, the inherent nature of LBSNs encourages users to publish information about their current location (i.e., their check-ins). The same is true for the majority of the most popular social networking websites, which offer the possibility of associating the current location of users to their posts and photos. Moreover, some LBSNs, such as Foursquare, let users tag their friends in their check-ins, thus potentially releasing location information of individuals that have no control over the published data. This raises additional privacy concerns for the management of location information in LBSNs. In this paper we propose and evaluate a series of techniques for the identification of users from their check-in data. More specifically, we first present two strategies according to which users are characterized by the spatio-temporal trajectory emerging from their check-ins over time and the frequency of visit to specific locations, respectively. In addition to these approaches, we also propose a hybrid strategy that is able to exploit both types of information. It is worth noting that these techniques can be applied to a more general class of problems where locations and social links of individuals are available in a given dataset. We evaluate our techniques by means of three real-world LBSNs datasets, demonstrating that a very limited amount of data points is sufficient to identify a user with a high degree of accuracy. For instance, we show that in some datasets we are able to classify more than 80% of the users correctly.

Networked gentrification:placemaking strategies and social networks of middle class gentrifiers in Istanbul

This chapter explores how gentrifiers in Istanbul mobilise their social networks and social capital during the gentrification process, and how their networks are constructed through processes of “ place making” and belonging. In addition, this chapter aims to demonstrate how social capital and social networks work in practice during the gentrification process. It also examines place making and claiming strategies of gentrifiers by focusing on the following questions: (a) What are the spatial strategies of the new middle class, and what is the importance of these strategies?; (b) How are class and spatial boundaries designated in gentrified neighbourhoods?; (c) What kinds of networks and relationships play a role in developing certain housing dispositions or belonging patterns

Examining factors associated with excess mortality in older people (age ≥ 70 years) with diabetes - a 10-year cohort study of older people with and without diabetes

Aims: To compare all-cause mortality in older people with or without diabetes and consider the associated risk of comorbidity and polypharmacy. Methods: A 10-year cohort study using data from the Health Innovation Network database (2003-2013) comparing mortality in people aged ≥ 70 years with diabetes (DM cohort) (n = 35 717) and without diabetes (No DM cohort) (n = 307 918). Results: The mean age of the DM cohort was 78.1 ± 5.8 years vs. 79.0 ± 6.3 years in the No DM cohort. Mean diabetes duration was 8.2 ± 8.1 years, and 30% had diabetes for > 10 years. The DM cohort had a greater comorbidity load and people in this cohort were prescribed more therapies than the No DM cohort. The 5- and 10-year survival rates were lower in the DM cohort at 64% and 39%, respectively, compared with 72% and 50% in the No DM cohort. The excess mortality in the DM cohort was greatest in those aged <75 years with longer duration diabetes, the relative hazard for mortality was higher in females. Although comorbidity and polypharmacy were associated with increased mortality risk in the DM cohort, this risk was lower compared with the No DM cohort. The hazard ratios (95% confidence interval) for comorbidities > 4 and medicines ≥ 7 were 1.29 (1.19 to 1.41) and 1.34 (1.25 to 1.43) in the DM cohort and 1.63 (1.57 to 1.70) and 1.48 (1.40 to 1.56) in the No DM cohort, respectively. Conclusions: There is significant excess mortality in older people with diabetes, which is unexplained by comorbidity or polypharmacy. This excess is greatest in the younger old with longer disease duration, suggesting that it may be related to the effect of diabetes exposure.

Association of anticholinergic burden with adverse effects in older people with intellectual disabilities:an observational cross-sectional study

BACKGROUND: No studies to date have investigated cumulative anticholinergic exposure and its effects in adults with intellectual disabilities. AIMS: To determine the cumulative exposure to anticholinergics and the factors associated with high exposure. METHOD: A modified Anticholinergic Cognitive Burden (ACB) scale score was calculated for a representative cohort of 736 people over 40 years old with intellectual disabilities, and associations with demographic and clinical factors assessed. RESULTS: Age over 65 years was associated with higher exposure (ACB 1-4 odds ratio (OR) = 3.28, 95% CI 1.49-7.28, ACB 5+ OR = 3.08, 95% CI 1.20-7.63), as was a mental health condition (ACB 1-4 OR = 9.79, 95% CI 5.63-17.02, ACB 5+ OR = 23.74, 95% CI 12.29-45.83). Daytime drowsiness was associated with higher ACB (P<0.001) and chronic constipation reported more frequently (26.6% ACB 5+ v. 7.5% ACB 0, P<0.001). CONCLUSIONS: Older people with intellectual disabilities and with mental health conditions were exposed to high anticholinergic burden. This was associated with daytime dozing and constipation.

Anticholinergic medication use and cognitive impairment in the older population:the Medical Research Council cognitive function and ageing study

OBJECTIVES: To determine whether the use of medications with possible and definite anticholinergic activity increases the risk of cognitive impairment and mortality in older people and whether risk is cumulative. DESIGN: A 2-year longitudinal study of participants enrolled in the Medical Research Council Cognitive Function and Ageing Study between 1991 and 1993. SETTING: Community-dwelling and institutionalized participants. PARTICIPANTS: Thirteen thousand four participants aged 65 and older. MEASUREMENTS: Baseline use of possible or definite anticholinergics determined according to the Anticholinergic Cognitive Burden Scale and cognition determined using the Mini-Mental State Examination (MMSE). The main outcome measure was decline in the MMSE score at 2 years. RESULTS: At baseline, 47% of the population used a medication with possible anticholinergic properties, and 4% used a drug with definite anticholinergic properties. After adjusting for age, sex, educational level, social class, number of nonanticholinergic medications, number of comorbid health conditions, and cognitive performance at baseline, use of medication with definite anticholinergic effects was associated with a 0.33-point greater decline in MMSE score (95% confidence interval (CI)=0.03–0.64, P=.03) than not taking anticholinergics, whereas the use of possible anticholinergics at baseline was not associated with further decline (0.02, 95% CI=-0.14–0.11, P=.79). Two-year mortality was greater for those taking definite (OR=1.68; 95% CI=1.30–2.16; P<.001) and possible (OR=1.56; 95% CI=1.36–1.79; P<.001) anticholinergics. CONCLUSION: The use of medications with anticholinergic activity increases the cumulative risk of cognitive impairment and mortality.

The importance of detecting and managing comorbidities in people with dementia?

Dementia is a debilitating condition characterised by global loss of cognitive and intellectual functioning, which gradually interferes with social and occupational performance. It is a common worldwide condition with a significant impact on society. There are currently 36 million people worldwide with Alzheimer's disease (AD) and other dementias [1]. This is expected to more than double by 2030 (65 million) and reach ∼115 million in 2050, unless a major breakthrough is made. The worldwide societal costs were estimated at USD 604 billion in 2010 and rising [2]. To date research on the specific physical healthcare needs of people with dementia has been neglected. Yet, physical comorbidities are reported as common in people with dementia [3] and have been shown to lead to increased disability and reduced quality of life for the affected person and their carer [4]. Dementia is most frequently associated with older people who often present with other medical conditions, known as co-morbidities. Such co-morbidities include diabetes, chronic obstructive pulmonary disorder, musculoskeletal disorders and chronic cardiac failure and are common, 61% of people with …

Indirect ties in knowledge networks:a social network analysis with ordered weighted averaging operators

This PhD thesis analyses networks of knowledge flows, focusing on the role of indirect ties in the knowledge transfer, knowledge accumulation and knowledge creation process. It extends and improves existing methods for mapping networks of knowledge flows in two different applications and contributes to two stream of research. To support the underlying idea of this thesis, which is finding an alternative method to rank indirect network ties to shed a new light on the dynamics of knowledge transfer, we apply Ordered Weighted Averaging (OWA) to two different network contexts. Knowledge flows in patent citation networks and a company supply chain network are analysed using Social Network Analysis (SNA) and the OWA operator. The OWA is used here for the first time (i) to rank indirect citations in patent networks, providing new insight into their role in transferring knowledge among network nodes; and to analyse a long chain of patent generations along 13 years; (ii) to rank indirect relations in a company supply chain network, to shed light on the role of indirectly connected individuals involved in the knowledge transfer and creation processes and to contribute to the literature on knowledge management in a supply chain. In doing so, indirect ties are measured and their role as means of knowledge transfer is shown. Thus, this thesis represents a first attempt to bridge the OWA and SNA fields and to show that the two methods can be used together to enrich the understanding of the role of indirectly connected nodes in a network. More specifically, the OWA scores enrich our understanding of knowledge evolution over time within complex networks. Future research can show the usefulness of OWA operator in different complex networks, such as the on-line social networks that consists of thousand of nodes.