Impacts of Hiding Friends’ Liked Content on User-Content Engagement across Newsfeed Channels

Social media platforms often distribute content through different newsfeed channels, most commonly, social networks, algorithmic recommendations and trending content. Prior literature has investigated each channel’s impact on user-content engagement. However, little is known about the relationships between these channels. We investigate the impacts of limiting content display from the social network channel on the quantity and diversity of user-engaged content across channels. We leverage a natural experiment, where a social media platform hides friends’ liked content from the social network channel, to identify the impacts. Results show that hiding friends’ liked content reduces the quantity of users’ content engagement on the entire platform. Across channels, users increase their engagement with trending content but decrease their engagement with algorithmic recommendations. Further, restricting exposure to friends’ liked content reduces the diversity of users’ content engagement. Our results highlight the intercorrelation of user-content engagement across newsfeed channels and provide insights for newsfeed designs

An Empirical Analysis of On-demand Ride Sharing and Traffic Congestion

Sharing economy, which leverages information technology to re-distribute unused or underutilized assets to people who are willing to pay for the services, has received tremendous attention in the last few years. Its creative business model has disrupted many traditional industries (e.g., transportation, hotel) by fundamentally changing the mechanism to facilitate the matching of demand with supply in real time. In this research, we investigate how Uber, a peer-to-peer mobile ride-sharing platform, affects traffic congestion in the urban areas of the United States. Combining data from Uber and the Urban Mobility Report, we empirically examine whether and how the entry of Uber car services affect traffic congestion using a difference-in-difference framework. Findings from this research provide evidence on the potential effect of ride sharing services in the transportation industry, contributing to the understanding of the sharing economy and government policy decisions

An Empirical Analysis of the Impacts of the Sharing Economy Platforms on the U.S. Labor Market

Each generation of digital innovation has caused a dramatic change in the way people work. Sharing economy is the latest trend of digital innovation, and it has fundamentally changed the traditional business models. In this paper, we empirically examine the impacts of the sharing economy platforms (specifically, Uber) on the labor market in terms of labor force participation, unemployment rate, supply, and wage of low-skilled workers. Combining a data set of Uber entry time and several microdata sets, we utilize a difference-in-differences (DID) method to investigate whether the above measures before and after Uber entry are significantly different across the U.S. metropolitan areas. Our empirical findings show that sharing economy platforms such as Uber significantly decrease the unemployment rate and increase the labor force participation. We also find evidence of a shift in the supply of low skill workers and consequently a higher wage rate for such workers in the traditional industries

An Economic Analysis of Subscription Sharing of Digital Services

Subscription sharing, where one shares her premium digital services subscription with other users, has become common due to subscription-sharing platforms like Togetherprice, Gowd, and Sharesub. This raises a question: Does it still make economic sense to offer a menu of subscription plans (e.g., an individual plan as well as a discounted family plan)? In this study, we look at a monopolist service provider that offers both plans but faces the potential threat of subscription sharing. We analyze the optimal prices and the impact of sharing on profit, customer surplus, and overall society benefits. Our results indicate that even with subscription sharing, offering both plans is at least as profitable as only offering individual plans. Under certain conditions, subscription sharing can even boost profits. Furthermore, our numerical analysis suggests that subscription sharing can benefit society. These findings suggest that subscription sharing is not necessarily as troublesome as one would have expected

Interaural Level Difference-Dependent Gain Control and Synaptic Scaling Underlying Binaural Computation

SummaryBinaural integration in the central nucleus of inferior colliculus (ICC) plays a critical role in sound localization. However, its arithmetic nature and underlying synaptic mechanisms remain unclear. Here, we showed in mouse ICC neurons that the contralateral dominance is created by a “push-pull”-like mechanism, with contralaterally dominant excitation and more bilaterally balanced inhibition. Importantly, binaural spiking response is generated apparently from an ipsilaterally mediated scaling of contralateral response, leaving frequency tuning unchanged. This scaling effect is attributed to a divisive attenuation of contralaterally evoked synaptic excitation onto ICC neurons with their inhibition largely unaffected. Thus, a gain control mediates the linear transformation from monaural to binaural spike responses. The gain value is modulated by interaural level difference (ILD) primarily through scaling excitation to different levels. The ILD-dependent synaptic scaling and gain adjustment allow ICC neurons to dynamically encode interaural sound localization cues while maintaining an invariant representation of other independent sound attributes

Robust and Intensity-Dependent Synaptic Inhibition Underlies the Generation of Non-monotonic Neurons in the Mouse Inferior Colliculus

Intensity and frequency are the two main properties of sound. The non-monotonic neurons in the auditory system are thought to represent sound intensity. The central nucleus of the inferior colliculus (ICC), as an important information integration nucleus of the auditory system, is also involved in the processing of intensity encoding. Although previous researchers have hinted at the importance of inhibitory effects on the formation of non-monotonic neurons, the specific underlying synaptic mechanisms in the ICC are still unclear. Therefore, we applied the in vivo whole-cell voltage-clamp technique to record the excitatory and inhibitory postsynaptic currents (EPSCs and IPSCs) in the ICC neurons, and compared the effects of excitation and inhibition on the membrane potential outputs. We found that non-monotonic neuron responses could not only be inherited from the lower nucleus but also be created in the ICC. By integrating with a relatively weak IPSC, approximately 35% of the monotonic excitatory inputs remained in the ICC. In the remaining cases, monotonic excitatory inputs were reshaped into non-monotonic outputs by the dominating inhibition at high intensity, which also enhanced the non-monotonic nature of the non-monotonic excitatory inputs