Since the end of the 20 th century, bees are suffering from increasing stress factors, leading domesticated colonies to die or at least be less productive. Precision beekeeping (PB) is an emerging field of agriculture that aims at protecting bees, supporting beekeepers, and optimizing apiary production thanks to digital infrastructures. The digitalization of apiculture first involves systems from the field of the Internet of Things (IoT), with the development of sensors to collect and transfer bee-related data. Then, data analysis comes into play, providing models that connect the data with the biological states of beehives, sometimes thanks to artificial intelligence (AI).In this paper, we describe the recent advances in precision beekeeping as systems and as services. Different types of sensors, networks, and power sources in PB are covered. The collection and use of data are described, and the performances of PB services are assessed. We also estimate the sustainability of the proposed solutions, taking into account their scalability, efficiency, and economic cost, because beekeepers need deployable research results.

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Previous studies indicated that active interactions on social networking services (SNS) are positively linked to subjective well-being (SWB). However, how semantic SNS content affects the association between the degree of SNS interaction and SWB has not been investigated. We addressed this issue by conducting a mediation analysis using natural language processing. We first analyzed Twitter data and SWB scores from 217 participants and found that the degree of active interactions on Twitter (i.e., frequency of reply) was positively correlated with SWB. Next, our multivariate mediation analysis demonstrated that positive words served as SWB-promoting mechanisms for highly interactive people, whereas worrying words led to lower SWB for less interactive people, but negative words did not. This study revealed that natural language content explains why individuals who are highly interactive on SNS have higher SWB, whereas less interactive individuals show lower SWB.