Adverse weather amplifies social media activity

Humanity spends an increasing proportion of its time interacting online. Scholars are intensively investigating the societal drivers and resultant impacts of this collective shift in our allocation of time and attention. Yet, the external factors that regularly shape online behavior remain markedly understudied. Do environmental factors alter rates of online activity? Here we show that adverse meteorological conditions markedly increase social media use in the United States. To do so, we employ climate econometric methods alongside over three and a half billion social media posts from tens of millions of individuals from both Facebook and Twitter between 2009 and 2016. We find that more extreme temperatures and added precipitation each independently amplify social media activity. Weather that is adverse on both the temperature and precipitation dimensions produces markedly larger increases in social media activity. On average across both platforms, compared to the temperate weather baseline, days colder than -5{\deg}C with 1.5-2cm of precipitation elevate social media activity by 35%. This effect is nearly three times the typical increase in social media activity observed on New Year's Eve in New York City. We observe meteorological effects on social media participation at both the aggregate and individual level, even accounting for individual-specific, temporal, and location-specific potential confounds

Seeing Eye to I? The Influence of Self-Video Display Size on Visual Attention and Collaborative Performance in Peer-to-Peer Video Chat

This thesis examines the influence of self-video size in video chat conversations on visual attention, collaborative performance, grounding, comfort and distraction during a brainstorming task. Twenty pairs of female university students were randomly assigned to either a large or small self-video condition. Two eye tracking systems were used to simultaneously record pairs of participants' gaze across 4 areas-of-interest spanning a 15-minute task. Participants with larger self-video gazed at themselves longer but did not spend a significantly different percentage of the conversation gazing at their partner. Participants sufficiently estimated how long they looked at each other, but significantly overestimated how long they, and their partners, gazed at their own self-video. A majority of participants found their self-video to be comforting, and participants with larger displays found it to be more distracting than those with smaller displays. Over a third of participants would prefer to chat without their self-video visible

Inferring transportation mode from smartphone sensors:Evaluating the potential of Wi-Fi and Bluetooth

Understanding which transportation modes people use is critical for smart cities and planners to better serve their citizens. We show that using information from pervasive Wi-Fi access points and Bluetooth devices can enhance GPS and geographic information to improve transportation detection on smartphones. Wi-Fi information also improves the identification of transportation mode and helps conserve battery since it is already collected by most mobile phones. Our approach uses a machine learning approach to determine the mode from pre-prepocessed data. This approach yields an overall accuracy of 89% and average F1 score of 83% for inferring the three grouped modes of self-powered, car-based, and public transportation. When broken out by individual modes, Wi-Fi features improve detection accuracy of bus trips, train travel, and driving compared to GPS features alone and can substitute for GIS features without decreasing performance. Our results suggest that Wi-Fi and Bluetooth can be useful in urban transportation research, for example by improving mobile travel surveys and urban sensing applications

Data Platforms and Cities

This section offers a series of joint reflections on (open) data platform from a variety of cases, from cycling, traffic and mapping to activism, environment and data brokering. Data platforms play a key role in contemporary urban governance. Linked to open data initiatives, such platforms are often proposed as both mechanisms for enhancing the accountability of administrations and performing as sites for 'bottom-up' digital invention. Such promises of smooth flows of data, however, rarely materialise unproblematically. The development of data platforms is always situated in legal and administrative cultures, databases are often built according to the standards of existing digital ecologies, access always involves processes of social negotiation, and interfaces (such as sensors) may become objects of public contestation. The following contributions explore the contested and mutable character of open data platforms as part of heterogeneous publics and trace the pathways of data through different knowledge, skills, public and private configurations. They also reflect on the value of STS approaches to highlight issues and tensions as well as to shape design and governance

The negative effect of smartphone use on academic performance may be overestimated: evidence from a two-year panel study

This study monitored 470 university students' smartphone usage continuously over two years to assess the relationship between in-class smartphone use and academic performance. We utilize a novel dataset where smartphone use and grades were recorded across multiple courses, allowing us to examine this relationship at the student level and the student-in-course level. In accordance with the existing literature, we find that students’ in-class smartphone use is negatively associated to their grades, even when controlling for a broad range of observed student characteristics. However, the magnitude of the association decreases substantially in a fixed effects model, which leverages the panel structure of the data to control for all stable student and course characteristics, including those not observed by researchers. This suggests that the size of the effect of smartphone usage on academic performance is overestimated by studies that only control for observed student characteristics

Data Platforms and Cities

International audienceThis section offers a series of joint reflections on (open) data platform from a variety of cases, from cycling, traffic and mapping to activism, environment and data brokering. Data platforms play a key role in contemporary urban governance. Linked to open data initiatives, such platforms are often proposed as both mechanisms for enhancing the accountability of administrations and performing as sites for 'bottom-up' digital invention. Such promises of smooth flows of data, however, rarely materialise unproblematically. The development of data platforms is always situated in legal and administrative cultures, databases are often built according to the standards of existing digital ecologies, access always involves processes of social negotiation, and interfaces (such as sensors) may become objects of public contestation. The following contributions explore the contested and mutable character of open data platforms as part of heterogeneous publics and trace the pathways of data through different knowledge, skills, public and private configurations. They also reflect on the value of STS approaches to highlight issues and tensions as well as to shape design and governance