Identifying influencers in a social network : the value of real referral data

Individuals influence each other through social interactions and marketers aim to leverage this interpersonal influence to attract new customers. It still remains a challenge to identify those customers in a social network that have the most influence on their social connections. A common approach to the influence maximization problem is to simulate influence cascades through the network based on the existence of links in the network using diffusion models. Our study contributes to the literature by evaluating these principles using real-life referral behaviour data. A new ranking metric, called Referral Rank, is introduced that builds on the game theoretic concept of the Shapley value for assigning each individual in the network a value that reflects the likelihood of referring new customers. We also explore whether these methods can be further improved by looking beyond the one-hop neighbourhood of the influencers. Experiments on a large telecommunication data set and referral data set demonstrate that using traditional simulation based methods to identify influencers in a social network can lead to suboptimal decisions as the results overestimate actual referral cascades. We also find that looking at the influence of the two-hop neighbours of the customers improves the influence spread and product adoption. Our findings suggest that companies can take two actions to improve their decision support system for identifying influential customers: (1) improve the data by incorporating data that reflects the actual referral behaviour of the customers or (2) extend the method by looking at the influence of the connections in the two-hop neighbourhood of the customers

From one-class to two-class classification by incorporating expert knowledge : novelty detection in human behaviour

One-class classification is the standard procedure for novelty detection. Novelty detection aims to identify observations that deviate from a determined normal behaviour. Only instances of one class are known, whereas so called novelties are unlabelled. Traditional novelty detection applies methods from the field of outlier detection. These standard one-class classification approaches have limited performance in many real business cases. The traditional techniques are mainly developed for industrial problems such as machine condition monitoring. When applying these to human behaviour, the performance drops significantly. This paper proposes a method that improves existing approaches by creating semi-synthetic novelties in order to have labelled data for the two classes. Expert knowledge is incorporated in the initial phase of this data generation process. The method was deployed on a real-life test case where the goal was to detect fraudulent subscriptions to a telecom family plan. This research demonstrates that the two-class expert model outperforms a one-class model on the semi-synthetic dataset. In a next step the model was validated on a real dataset. A fraud detection team of the company manually checked the top predicted novelties. The results show that incorporating expert knowledge to transform a one-class problem into a two-class problem is a valuable method

Determinants of body fatness in young adults living in a Dutch community

In 1979, the Department of Human Nutrition of the Agricultural University at Wageningen began a research project on obesity in young adults. The main objectives of this project are the investigation of aetiological aspects and health consequences of obesity. It is a prospective study and is being carried out in a young adult population of three age groups (19-21, 24-26 and 29-31 years as at 1 January 1980) in the Municipality of Ede. The present thesis deals with the investigations into determinants of body fatness and two methodological studies concerning relative weight and habitual physical activity which form the first part of the research project mentioned above.In the Introduction, a general survey is given of the methods of measuring body fatness. Health consequences and aetiology of obesity are also surveyed. Approximately 3900 subjects participated in the studies described in Chapter 2 and 3, and a subsample of approximately 300 subjects from the initial population participated in the studies described in Chapters 4-6.The relationship between various socio-demographic variables and body mass index (BMI; weight/height 2) is dealt with in Chapter 2. The prevalence of severe obesity (BMI ≥30.0 kg/m 2) was 2% in both sexes. The most salient socio-demographic determinants of BMI were age and level of education. Older subjects were heavier, and subjects who had a higher level of education were lighter. Other socio-demographic determinants of BMI were: level of father's occupation and religion in both sexes; parity in females; and urbanization and church attendance in males.The relationship between aspects of daily life-style and BMI are described in Chapter 3. Five conceptually meaningful factors could be distinguished within the aspects of daily life-style considered. These factors were interpreted as constructs of: 1, slimming behaviour; 2, behaviour characterized by the consumption of coffee and alcohol, smoking habits and number of hours of sleep per night (CASS behaviour); 3, eating sweet and savoury snacks; 4, health-conscious behaviour; and 5, physical activity. Heavier subjects had higher ratings for slimming behaviour and lower ratings for health-conscious behaviour. In addition heavier males had higher ratings for CASS behaviour.Possible improvement in the prediction of body fatness when an index of relative weight is based not only on body weight and body height, but also on frame size, is considered in Chapter 4. The prediction of body fatness was not improved when frame size, as assessed by knee width and wrist width, was taken into account. BMI was the most preferable of the indices considered.The development of a short questionnaire for the measurement of habitual physical activity is discussed in Chapter 5. Three dimensions could be distinguished within the pattern of habitual physical activity. They are interpreted as: 1, physical activity at work; 2, sport during leisure time; and 3, physical activity during leisure time excluding sport. Level of education was inversely related to physical activity at work, and positively related to physical activity during leisure time excluding sport. Subjective experience of work load was inversely related to both sport and other physical activities during leisure time. Lean body mass was positively related to both physical activity at work and sport, in males only.The relationship between body fatness and both food consumption and habitual physical activity are dealt with in Chapter 6. The average daily energy intake in males was rather high (about 3000 kcal) and average body weight increased by 1.2 kg in the preceding year. Both findings suggest the existence of a positive energy balance. In females the average daily energy intake of about 2170 kcal was closer to the recommended intake and average body weight remained constant. There were no important differences in the pattern of habitual physical activity between the categories of body fatness defined. However the daily energy intake of fatter subjects was lower than that of leaner subjects. This finding may be explained by a reduction of food intake in fatter subjects in an attempt to reduce body weight. There is also some evidence to suggest that many fatter subjects have a reduced need for energy, but it is not clear whether this is a causal factor of obesity or an effect of prolonged slimming.Finally, a general discussion of the results is given in Chapter 7. While some of the findings can be useful for the management of obesity. it must be emphasized, that several aspects have yet to be studied in detail in the research project of which this thesis forms the first part

Body fatness, relative weight and frame size in young adults

1. Body-weight, body height, knee width, wrist width and skinfold measurements were made on males (n 139) and females (n 167) in three age-groups (20–22, 25–27 and 30–32 years). Percentage of body fal was calculated from skinfold thicknesses using regression equations according to Durnin & Womersley (1974), Three indices of relative weight were calculated: W/H2, W/Hp and W/Ŵ, where W is body-weight, H is body height, p is the exponent that made the index of relative weight independent of height and W is the weight, estimated from body height and frame size. 2. The standard error of the estimate of body-weight was only reduced by 5% in males and by 13% in females when, in addition to body height, knee width was taken into account.The addition of wrist width did not improve the accuracy of estimation of body-weight in either sex. Therefore in further analyses W was estimated from body height and knee width. In the present population the exponent p was 1·7 in males and 1·6 in females. 3. The correlations between the percentage of body fat and the indices, W/H2, W/HP, and W/Ŵ, were all very similar, being approximately 0·8 in both sexes. 4. A positive relationship was observed between percentage of body fat and knee width in females, which may be explained by an artifact of measurement. 5. In conclusion it can be stated that the accuracy of estimation of percentage of body fat was not improved when the index of relative weight was adjusted for knee width or wrist width in the present population. The W/H2was the most preferable of the three indices which were calculated

Are older adults with chronic musculoskeletal pain less active than older adults without pain? A systematic review and meta-analysis.

Objective: To compare the overall levels of physical activity of older adults with chronic musculoskeletal pain and asymptomatic controls. Review Methods: A systematic review of the literature was conducted using a Cochrane methodology and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Major electronic databases were searched from inception until December 2012, including the Cochrane Library, CINAHL, EBSCO, EMBASE, Medline, PubMed, PsycINFO, and the international prospective register of systematic reviews. In addition, citation chasing was undertaken, and key authors were contacted. Eligibility criteria were established around participants used and outcome measures focusing on daily physical activity. A meta-analysis was conducted on appropriate studies. Results: Eight studies met the eligibility criteria, four of these reported a statistically lower level of physical activity in the older adult sampl e with chronic pain compared with the asymptomatic group. It was possible to perform a non-heterogeneous meta-analysis on five studies. This established that 1,159 older adults with chronic pain had a significantly lower level of physical activity (−0.20, confidence interval 95% = −0.34 to −0.06, p = 0.004) compared with 576 without chronic pain. Conclusion: Older adults with chronic pain appear to be less active than asymptomatic controls. Although this difference was small, it is likely to be clinically meaningful. It is imperative that clinicians encourage older people with chronic pain to remain active as physical activity is a central non-pharmacological strategy in the management of chronic pain and is integral for healthy aging. Future research should prioritize the use of objective measurement of physical activity

Glycated Hemoglobin and the Risk of Kidney Disease and Retinopathy in Adults With and Without Diabetes

10.2337/db10-1198Diabetes601298-305DIAE

Association of the Joint Effect of Menopause and Hormone Replacement Therapy and Cancer in African American Women: The Jackson Heart Study

Cancer is the second leading cause of death in the US and in Mississippi. Breast cancer (BC) is the most common cancer among women, and the underlying pathophysiology remains unknown, especially among African American (AA) women. The study purpose was to examine the joint effect of menopause status (MS) and hormone replacement therapy (HRT) on the association with cancers, particularly BC using data from the Jackson Heart Study. The analytic sample consisted of 3202 women between 35 and 84 years of which 73.7% and 22.6% were postmenopausal and on HRT, respectively. There were a total of 190 prevalent cancer cases (5.9%) in the sample with 22.6% breast cancer cases. Menopause (p < 0.0001), but not HRT (p = 0.6402), was independently associated with cancer. Similar results were obtained for BC. BC, cancer, hypertension, type 2 diabetes, prevalent cardiovascular disease, physical activity and certain dietary practices were all significantly associated with the joint effect of menopause and HRT in the unadjusted analyses. The family history of cancer was the only covariate that was significantly associated with cancer in the age-adjusted models. In examining the association of cancer and the joint effect of menopause and HRT, AA women who were menopausal and were not on HRT had a 1.97 (95% CI: 1.15, 3.38) times odds of having cancer compared to pre-menopausal women after adjusting for age; which was attenuated after further adjusting for family history of cancer. Given that the cancer and BC cases were small and key significant associations were attenuated after adjusting for the above mentioned covariates, these findings warrant further investigation in studies with larger sample sizes of cancer (and BC) cases