Taste or Addiction?: Using Play Logs to Infer Song Selection Motivation

Online music services are increasing in popularity. They enable us to analyze people's music listening behavior based on play logs. Although it is known that people listen to music based on topic (e.g., rock or jazz), we assume that when a user is addicted to an artist, s/he chooses the artist's songs regardless of topic. Based on this assumption, in this paper, we propose a probabilistic model to analyze people's music listening behavior. Our main contributions are three-fold. First, to the best of our knowledge, this is the first study modeling music listening behavior by taking into account the influence of addiction to artists. Second, by using real-world datasets of play logs, we showed the effectiveness of our proposed model. Third, we carried out qualitative experiments and showed that taking addiction into account enables us to analyze music listening behavior from a new viewpoint in terms of how people listen to music according to the time of day, how an artist's songs are listened to by people, etc. We also discuss the possibility of applying the analysis results to applications such as artist similarity computation and song recommendation.Comment: Accepted by The 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2017

Religious people only live longer in religious cultural contexts: A gravestone analysis.

Religious people live longer than non-religious people according to a staple of social science research. Yet, are those longevity benefits an inherent feature of religiosity? To find out, we coded gravestone inscriptions and imagery in order to assess the religiosity and longevity of 6,400 deceased people from religious and non-religious U.S. counties. We show that in religious cultural contexts, religious people lived 2.2 years longer than did non-religious people. In non-religious cultural contexts, however, religiosity conferred no such longevity benefits. Evidently, a longer life is not an inherent feature of religiosity. Instead, religious people only live longer in religious cultural contexts where religiosity is valued. Our study answers a fundamental question on the nature of religiosity and showcases the scientific potential of gravestone analyses

Fear, populism, and the geopolitical landscape: the “sleeper effect” of neurotic personality traits on regional voting behavior in the 2016 Brexit and Trump elections

Two recent electoral results - Donald Trump’s election as US president and the UK’s Brexit vote - have re-ignited debate on the psychological factors underlying voting behavior. Both campaigns promoted themes of fear, lost pride, and loss aversion, which are relevant to the personality dimension of Neuroticism, a construct previously not associated with voting behavior. To that end, we investigate whether regional prevalence of neurotic personality traits (Neuroticism, Anxiety, Depression) predicted voting behavior in the US (N = 3,167,041) and the UK (N = 417,217), comparing these effects with previous models, which have emphasized the roles of Openness and Conscientiousness. Neurotic traits positively predicted share of Brexit and Trump votes and Trump gains from Romney. Many of these effects persisted in additional robustness tests controlling for regional industrial heritage, political attitude, and socio-economic features, particularly in the US. The “sleeper effect” of neurotic traits may profoundly impact the geopolitical landscape

Does Shyness Vary According to Attained Social Roles? Trends Across Age Groups in a Large British Sample

OBJECTIVE: The current study investigated (a) how a composite measure of shyness comprising introversion and neuroticism relates to other well-known constructs involving social fears, and (b) whether mean levels of shyness vary for men and women depending on the adoption of various social roles. METHOD: Study 1 used a sample of 211 UK participants aged 17–70 (64% female; Mage = 47.90). Study 2 used data from a large cross-sectional data set with UK participants aged 17–70 (Ntarget = 552,663; 64% female; Mage = 34.19 years). RESULTS: Study 1 showed that shyness measured as a composite of introversion and neuroticism was highly correlated with other constructs involving social fears. Study 2 indicated that, controlling for various sociodemographic variables, females appeared to have higher levels, whereas males appeared to have lower levels of shyness. Males and females who were in employment had the lowest shyness levels, whereas those working in unskilled jobs had the highest levels and people working in sales the lowest levels of shyness. Participants in relationships had lower levels of shyness than those not in relationships, but parenthood was not associated with shyness. CONCLUSIONS: Mean levels of shyness are likely to vary according to adopted social roles, gender, and age.Preparation of this manuscript was supported by Grant 2011-0307 from the Swedish Research Council for Health, Working Life and Welfare to Nejra Van Zalk

Alleviating the new user problem in collaborative filtering by exploiting personality information

The final publication is available at Springer via http://dx.doi.org/10.1007/s11257-016-9172-zThe new user problem in recommender systems is still challenging, and there is not yet a unique solution that can be applied in any domain or situation. In this paper we analyze viable solutions to the new user problem in collaborative filtering (CF) that are based on the exploitation of user personality information: (a) personality-based CF, which directly improves the recommendation prediction model by incorporating user personality information, (b) personality-based active learning, which utilizes personality information for identifying additional useful preference data in the target recommendation domain to be elicited from the user, and (c) personality-based cross-domain recommendation, which exploits personality information to better use user preference data from auxiliary domains which can be used to compensate the lack of user preference data in the target domain. We benchmark the effectiveness of these methods on large datasets that span several domains, namely movies, music and books. Our results show that personality-aware methods achieve performance improvements that range from 6 to 94 % for users completely new to the system, while increasing the novelty of the recommended items by 3-40 % with respect to the non-personalized popularity baseline. We also discuss the limitations of our approach and the situations in which the proposed methods can be better applied, hence providing guidelines for researchers and practitioners in the field.This work was supported by the Spanish Ministry of Economy and Competitiveness (TIN2013-47090-C3). We thank Michal Kosinski and David Stillwell for their attention regarding the dataset

Understanding the Role of Places and Activities on Mobile Phone Interaction and Usage Patterns

User interaction pa erns with mobile apps and noti cations are generally complex due to the many factors involved. However a deep understanding of what in uences them can lead to more acceptable applications that are able to deliver information at the right time. In this paper, we present for the rst time an in-depth analysis of interaction behavior with noti cations in relation to the location and activity of users. We conducted an in-situ study for a period of two weeks to collect more than 36,000 noti cations, 17,000 instances of application usage, 77,000 location samples, and 487 days of daily activity entries from 26 students at a UK university. Our results show that users’ a ention towards new noti cations and willingness to accept them are strongly linked to the location they are in and in minor part to their current activity. We consider both users’ receptivity and a entiveness, and we show that di erent response behaviors are associated to di erent locations. ese ndings are fundamental from a design perspective since they allow us to understand how certain types of places are linked to speci c types of interaction behavior. is information can be used as a basis for the development of novel intelligent mobile applications and services.EPSRC UBHAV

Music listening in everyday life: Devices, selection methods, and digital technology

Two studies considered whether psychological variables could predict everyday music listening practices more than those demographic and technology-related variables studied predominantly hitherto. Study 1 focused on music-listening devices, while Study 2 focused on music selection strategies (e.g. playlists). Study 1 indicated the existence of a one-dimensional identity based on music technology. Further, psychological variables (such as innovativeness and self-efficacy) predicted whether individuals possess such an identity. Moreover, while psychological variables predicted whether individuals preferred ‘familiarized’ advantages inherent to listening devices, a preference for ‘progressive’ advantages was predicted by technological behaviors. Study 2 supported the first study in terms of identity, and demonstrated that a different pattern of variables predicted playlist listening from listening to music via shuffle. More generally, the findings suggest the utility of applying constructs from consumer psychology to everyday music-listening behaviors

Tune in to your emotions: a robust personalized affective music player

The emotional power of music is exploited in a personalized affective music player (AMP) that selects music for mood enhancement. A biosignal approach is used to measure listeners’ personal emotional reactions to their own music as input for affective user models. Regression and kernel density estimation are applied to model the physiological changes the music elicits. Using these models, personalized music selections based on an affective goal state can be made. The AMP was validated in real-world trials over the course of several weeks. Results show that our models can cope with noisy situations and handle large inter-individual differences in the music domain. The AMP augments music listening where its techniques enable automated affect guidance. Our approach provides valuable insights for affective computing and user modeling, for which the AMP is a suitable carrier application

You Know What It Is: Learning Words through Listening to Hip-Hop

Music listeners have difficulty correctly understanding and remembering song lyrics. However, results from the present study support the hypothesis that young adults can learn African-American English (AAE) vocabulary from listening to hip-hop music. Non-African-American participants first gave free-response definitions to AAE vocabulary items, after which they answered demographic questions as well as questions addressing their social networks, their musical preferences, and their knowledge of popular culture. Results from the survey show a positive association between the number of hip-hop artists listened to and AAE comprehension vocabulary scores. Additionally, participants were more likely to know an AAE vocabulary item if the hip-hop artists they listen to use the word in their song lyrics. Together, these results suggest that young adults can acquire vocabulary through exposure to hip-hop music, a finding relevant for research on vocabulary acquisition, the construction of adolescent and adult identities, and the adoption of lexical innovations

Experimental effects of climate messages vary geographically

Social science scholars routinely evaluate the efficacy of diverse climate frames using local convenience or nationally representative samples. For example, previous research has focused on communicating the scientific consensus on climate change, which has been identified as a ‘gateway’ cognition to other key beliefs about the issue6,7,8,9. Importantly, although these efforts reveal average public responsiveness to particular climate frames, they do not describe variation in message effectiveness at the spatial and political scales relevant for climate policymaking. Here we use a small-area estimation method to map geographical variation in public responsiveness to information about the scientific consensus as part of a large-scale randomized national experiment (n = 6,301). Our survey experiment finds that, on average, public perception of the consensus increases by 16 percentage points after message exposure. However, substantial spatial variation exists across the United States at state and local scales. Crucially, responsiveness is highest in more conservative parts of the country, leading to national convergence in perceptions of the climate science consensus across diverse political geographies. These findings not only advance a geographical understanding of how the public engages with information about scientific agreement, but will also prove useful for policymakers, practitioners and scientists engaged in climate change mitigation and adaptation.MacArhur Foundation, Energy Foundatio