Incentivising Use of Structured Language in Biological Descriptions: Author-Driven Phenotype Data and Ontology Production

Phenotypes are used for a multitude of purposes such as defining species, reconstructing phylogenies, diagnosing diseases or improving crop and animal productivity, but most of this phenotypic data is published in free-text narratives that are not computable. This means that the complex relationship between the genome, the environment and phenotypes is largely inaccessible to analysis and important questions related to the evolution of organisms, their diseases or their response to climate change cannot be fully addressed. It takes great effort to manually convert free-text narratives to a computable format before they can be used in large-scale analyses. We argue that this manual curation approach is not a sustainable solution to produce computable phenotypic data for three reasons: 1) it does not scale to all of biodiversity; 2) it does not stop the publication of free-text phenotypes that will continue to need manual curation in the future and, most importantly, 3) It does not solve the problem of inter-curator variation (curators interpret/convert a phenotype differently from each other). Our empirical studies have shown that inter-curator variation is as high as 40% even within a single project. With this level of variation, it is difficult to imagine that data integrated from multiple curation projects can be of high quality. The key causes of this variation have been identified as semantic vagueness in original phenotype descriptions and difficulties in using standardised vocabularies (ontologies). We argue that the authors describing phenotypes are the key to the solution. Given the right tools and appropriate attribution, the authors should be in charge of developing a project’s semantics and ontology. This will speed up ontology development and improve the semantic clarity of phenotype descriptions from the moment of publication. A proof of concept project on this idea was funded by NSF ABI in July 2017. We seek readers input or critique of the proposed approaches to help achieve community-based computable phenotype data production in the near future. Results from this project will be accessible through https://biosemantics.github.io/author-driven-production

Predictors of social media self-control failure: Immediate gratifications, habitual checking, ubiquity and notifications

Social media users often experience the difficulty of controlling their social media use while having important tasks to do. Recent theorizing on self-control and media use proposes four possible factors (immediate gratifications, habitual checking, ubiquity, and notifications) that might cause social media self-control failure (SMSCF). We tested whether these factors indeed predict SMSCF among 590 daily social media users. Results showed that, when people checked social media habitually, or strongly experienced the online ubiquity of social media, or perceived strong disturbances from social media notifications, they were more likely to fail to control their social media use. However, social media-related immediate gratifications did not predict SMSCF. This study empirically identified social media-related factors that might induce social media users' self-control difficulty

The Effects of Feedback and Habit on Content Posting in an Online Community

This study examined the relationship between feedback and content posting behavior in the social media system Everything2. Analyses paired survey data with behavioral data of user activity obtained from server logs. Results showed that both positive and negative feedback from other users was associated with more posting behavior. Habit strength moderated the effect of positive feedback such that those with higher habit were less affected by the feedback than those with lower habit. Habit, however, did not moderate the effect of negative feedback. Results suggest that systems that facilitate positive feedback mechanisms may encourage initial participation but may become less effective for users who have developed a habit.ye

EXAMINING CONSTRUAL LEVEL PRIMING AS A POTENTIONAL INTERVENTION FOR MISINFORMATION SHARING

Misinformation has become increasingly difficult to combat in the digital age. The current study tested a model exploring the relationships between self-regulation, habitual social media use, construal level, and propagation of misinformation. Drawing from previous research, I hypothesized that individuals with higher self-regulation would exhibit lower susceptibility to misinformation sharing. I also hypothesized that habitual social media use mediates the relationship between self-regulation and misinformation sharing. In addition, I introduced construal level priming as an experimental intervention, where individuals primed with abstract construal levels may demonstrate more discerning information processing, thereby reducing the likelihood of misinformation sharing. Results from data analyses indicated that self-regulation is negatively associated with misinformation sharing. However, habitual media usage did not mediate the relationship between self-regulation and misinformation sharing, and construal level priming did not moderate the relationship between self-regulation and misinformation sharing, and between habitual social media usage and misinformation sharing. Potential causes of these non-significant associations are discussed

Participation of young people in online social communities: an exploration of attitudes among university students in a case study in Spain

This study aims to examine the different dimensions of online citizen participation for the purpose of delving into the types of engagement that are being developed in order for citizens to benefit from the opportunities offered by the Internet. A self-administered survey has been carried out with 420 students from a Spanish public University (Universidad Rey Juan Carlos) from its five campuses in Madrid. A typology of attitudes has been developed, firstly with factor analysis, and then with a varimax rotation. Moreover, a hierarchical linear regression has been applied in order to discover the variables that might predict the typology of participation. The study shows that online participation is a complex phenomenon influenced by multiple personal and social factors. The results have revealed three points of view: 1. Scepticism toward the ability to exert influence; 2. Social networks as a channel for maintaining social contact and expressing opinions; and 3. Capability of empowering users. Certain attitudes toward social networks can predict online participatory behaviour in different types of profiles on these networks. Furthermore, age does not affect online participation, and gender only has an influence on sports and media profiles

Characterizing Novelty as a Motivator in Online Citizen Science

Citizen science projects rely on the voluntary contribution of nonscientists to take part in scientific research projects. Projects taking place exclusively over the Internet face significant challenges, chief among them is the attracting and keeping the critical mass of volunteers needed to conduct the work outlined by the science team. The extent to which platforms can design experiences that positively influence volunteers’ motivation can help address the contribution challenges. Consequently, project organizers need to develop strategies to attract new participants and keep existing ones. One strategy to encourage participation is implementing features, which re-enforce motives known to change people’s attitudes towards contributing positively. The literature in psychology noted that novelty is an attribute of objects and environments that occasion curiosity in humans leading to exploratory behaviors, e.g., prolonged engagement with the object or environment. This dissertation described the design, implementation, and evaluation of an experiment conducted in three online citizen science projects. Volunteers received novelty cues when they classified data objects that no other volunteer had previously seen. The hypothesis was that exposure to novelty cues while classifying data positively influences motivational attitudes leading to increased engagement in the classification task and increased retention. The experiments resulted in mixed results. In some projects, novelty cues were universally salient, and in other projects, novelty cues had no significant impact on volunteers’ contribution behaviors. The results, while mixed, are promising since differences in the observed behaviors arise because of individual personality differences and the unique attributes found in each project setting. This research contributes to empirically grounded studies on motivation in citizen science with analyses that produce new insights and questions into the functioning of novelty and its impact on volunteers’ behaviors

Digital Behaviour Change Interventions to Break and Form Habits

Digital behaviour change interventions, particularly those using pervasive computing technology, hold great promise in supporting users to change their behaviour. However, most interventions fail to take habitual behaviour into account, limiting their potential impact. This failure is partly driven by a plethora of overlapping behaviour change theories and related strategies that do not consider the role of habits. We critically review the main theories and models used in the research to analyse their application to designing effective habitual behaviour change interventions. We highlight the potential for Dual Process Theory, modern habit theory, and Goal Setting Theory, which together model how users form and break habits, to drive effective digital interventions. We synthesise these theories into an explanatory framework, the Habit Alteration Model, and use it to outline the state of the art. We identify the opportunities and challenges of habit-focused interventions.</jats:p

Targeting the automatic: Nonconscious behaviour change using technology

Digital interventions have great potential to support people to change their behaviour. However, most interventions focus on strategies that target limited conscious resources, reducing their potential impact. We outline how these may fail in the longer-term due to issues with theory, users and technology. We propose an alternative: the direct targeting of nonconscious processes to achieve behaviour change. We synthesise Dual Process Theory, modern habit theory and Goal Setting Theory, which together model how users form and break nonconscious behaviours, into an explanatory framework to explore nonconscious behaviour change interventions. We explore the theoretical and practical implications of this approach, and apply it to a series of empirical studies. The studies explore nonconscious-targeting interventions across a continuum of conscious attention required at the point of behavioural action, from high (just-in-time reminders within Implementation Intentions) to medium (training paradigms within cognitive bias modification) to low (subliminal priming). The findings show that these single-nonconscious-target interventions have mixed results in in-the-wild and semi-controlled conditions. We conclude by outlining how interventions might strategically deploy multiple interventions that target the nonconscious at differing levels of conscious attention, and by identifying promising avenues of future research