- Suddenness of human physical activity and its characterization;
- Online force-oriented algorithm for dynamic graph visualization;
- Characterize urban lifestyle characteristics using model attributes in a network of locations;
- Dynamics of competitive social contagion: symmetrical disruption and equilibrium uncertainty;
- Develop current estimated household data and simulations of the future population distribution of Japanese households based on subjects;
- VaccinEU: COVID-19 vaccine conversations in French, German and Italian on Twitter;
- Detect false rumors from the turbulence on social media;
- Shared user interfaces for physiological data: a systematic review of social biofeedback systems and contexts in human-computer interaction;
- Based on machine learning to reveal real-world CO2 emission reductions and determinants of ride-sharing;
- Maon? caricature? Characterize spontaneous creative competitions on social media;
- Whose advantage? Measure attention dynamics on controversial topics on YouTube and Twitter;
- Aging effects in Schelling separation models;
Suddenness of human physical activity and its characterization
原文标题： Burstiness of human physical activities and their characterization
Address: http://arxiv.org/abs/2204.00201
By Makoto Takeuchi, Yukie Sano
Abstract: It is well known that human behavior is heterogeneous and fluctuates over time. Many studies have focused on fluctuations in inter-event time (IET), the time between one action and the next in various human behaviors. The presence of such fluctuations cannot be explained by a smooth, random Poisson process, called burstiness. In this study, we collected data on human physical activity while specifying the subjects' ages and their condition (e.g., children's games and adult chores), and analyzing their time series of events. We confirmed the suddenness of children and adults. In particular, for the first time, explosive physical activity in children aged 2-3 years was observed to the best of our knowledge. We also confirmed that each activity situation has its own specific IET distribution characteristics. Our findings may provide important clues to identifying the sudden mechanisms of human physical activity.
Online force-directed algorithm for dynamic graph visualization
原文标题： Online force-directed algorithms for visualization of dynamic graphs
Address: http://arxiv.org/abs/2204.00451
By Se-Hang Cheong, Yain-Whar Si
Summary: Force-directed (FD) algorithms can be used to explore relationships in social networks, visualize currency markets, and analyze trading networks. However, the FD algorithm is primarily used to visualize static graphs, where the topology of the network remains the same throughout the calculation. In contrast to static graphs, nodes and edges in dynamic graphs can be added or removed over time. In these cases, existing FD algorithms do not scale well, because any change in topology will trigger these algorithms to completely restart the entire computation. To alleviate this problem, we propose the design and implementation of five online FD algorithms to visualize dynamic graphs while maintaining their native forces model. The online FD algorithm developed in this article is capable of reusing the force model of an existing FD algorithm without major modifications. To assess the effectiveness of the proposed method, the online FD algorithm is compared with the static FD algorithm used to visualize the dynamic graph. Experimental results show that among the five algorithms evaluated, the online FD algorithm achieves the optimal number of edge crosses and the standard deviation of edge length for visualizing dynamic graphs.
Use mold attributes in a network of locations to characterize urban lifestyles
原文标题： Characterizing Urban Lifestyle Signatures Using Motif Properties in Network of Places
Address: http://arxiv.org/abs/2204.01103
By Junwei Ma, Bo Li, Ali Mostafavi
Abstract: The lifestyles of city dwellers can reveal important insights into the dynamics and complexity of cities. Despite the growing number of studies on the analysis of urban lifestyle patterns, little is known about the characteristics of urban-scale lifestyle patterns. This limitation is mainly due to the challenges encountered in describing lifestyle patterns when aggregating human motion data to protect user privacy. In this study, we modeled cities based on aggregated human access data to build a network of locations. We then examine sub-map symbols in the network of locations to plot and describe lifestyle patterns on a city scale. Location-based data from Harris, Dallas, New York, and Broward counties were examined to reveal the lifestyle characteristics of cities. For topic analysis, two-node, three-node, and four-node topics with no location attributes were extracted from the human access network. Second, the homogenized nodes in the mold are encoded using the location categories from the NAICS code. Multiple statistical measurements, including network metrics and thematic attributes, are quantified to characterize lifestyle characteristics. The results show that based on the distribution and attributes of the themes in the location network, people's lifestyles in the urban environment can be well described and quantified; the themes in the location network show the stability of the number and distance and the periodicity of weekends and weekdays, indicating the stability of urban lifestyle patterns; human access networks and lifestyle patterns show similarities in different metropolitan areas, which means the universality of different urban lifestyle characteristics. These findings provide deeper insights into urban lifestyle characteristics in urban studies and important insights into data-based urban planning and management.
Dynamics of competitive social contagion: symmetrical disruption and equilibrium uncertainty
原文标题： Kinetics of competing social contagions: Symmetry breaking and equilibrium indeterminacy
Address: http://arxiv.org/abs/2204.00804
Author: Teruyoshi Kobayashi
Summary: Complex contagion on social networks is interpreted as a collective consequence of threshold behavior, where influences from local neighbors can trigger a global cascade. However, much has not yet been explored which behavioral rules best describe an individual's optimization and how to generate propagation dynamics from them. Here, we develop a micro-foundation-based generic threshold model that allows us to analyze the collective dynamics of individual behavior in the spread of competitive information/technology (i.e., "social memes"). The analysis showed that the prevalence of competing memes in finite size systems was uncertain because the propagation process followed a saddle path, leading to a breakdown of symmetry. This suggests that the viral spread of social memes may be attributed not to their intrinsic attractiveness, but to the randomness of the network structure.
Develop current estimated household data and simulations of the future population distribution of Japanese households based on subjects
原文标题： Development of current estimated household data and agent-based simulation of the future population distribution of households in Japan
Address: http://arxiv.org/abs/2204.00198
作者： Kajiwara Kento, Jue Ma, Toshikazu Seto, Yoshihide Sekimoto, Yoshiki Ogawa, Hiroshi Omata
Abstract: In response to Japan's declining population and aging infrastructure, local governments are implementing compact urban policies, such as location normalization programs. In order to optimize the restructuring of urban public infrastructure, it is important to make detailed and accurate predictions of the distribution of urban population and households. However, many local governments do not have the necessary data and forecasting capabilities. In addition, current projections of gender- and age-based population data exist only at municipal levels, while household data exist only in household types in prefecture-level cities. At the same time, assuming that the rate of population change is the same in all municipalities and within each city, accuracy is limited. Therefore, the purpose of this study is to develop a subject-based micro-simulated family transformation model that estimates household data in all cities in Japan from 2015 onwards, using households as units and subjects. Estimated household data include household type, type, address, age and sex of family members that houses obtain from the national census and construction data. The resulting family transition model is used to predict the attributes of each family every five years. Simulations of Toyama Prefecture and Shizuoka Prefecture in Japan from 1980 to 2010 provide highly accurate estimates of the municipal population by age and family type. The proposed model has also been applied to predict the future distribution of disappearing villages and vacant houses in Japan.
VaccinEU: Covid-19 Vaccine Conversations in French, German and Italian on Twitter
原文标题： VaccinEU: COVID-19 vaccine conversations on Twitter in French, German and Italian
Address: http://arxiv.org/abs/2201.06293
作者: Marco Di Giovanni, Francesco Pierri, Christopher Torres-Lugo, Marco Brambilla
Summary: Despite increasing restrictions on unvaccinated people, in many European countries, there is still a non-negligible number of people who refuse to vaccinate against SARS-CoV-2, thus undermining government efforts to eradicate the virus. We study the role of online social media in influencing individuals' perceptions of vaccinations by designing a large-scale collection of Twitter messages in three different languages (French, German, and Italian) and providing public access to the data collected. Our VaccinEU dataset looks at the European context and is designed to help researchers better understand the impact of online (misleading) information about vaccines and design more accurate communication strategies to maximize vaccination coverage.
Detect false rumors from the whirling state on social media
原文标题： Detecting False Rumors from Retweet Dynamics on Social Media
Address: http://arxiv.org/abs/2201.13103
By Christof Naumzik, Stefan Feuerriegel
Abstract: As we all know, false rumors can adversely affect society. To prevent the spread of false rumors, social media platforms such as Twitter must detect them early. In this work, we developed a novel probabilistic hybrid model that classifies true and false rumors based on potential propagation processes. Specifically, our model is the first to formalize the self-excited nature of the real and spurious forwarding processes. This led to a new hybrid labeled Hawkes model (MMHM). Therefore, our model does not require feature engineering; instead, it directly models the propagation process to infer whether the online rumor is wrong or not. Our assessment is based on 13,650 retweet cascades, both of which are true. With false rumors from Twitter. Our model identifies false rumors with a balanced accuracy of 64.97% and a 69.46% AUC. It is considerably superior to state-of-the-art baselines (neural and feature engineering), but at the same time is fully interpretable. Our work has a direct impact on practitioners: it uses the propagation process as an implicit quality signal and detects false content on that basis.
Shared User Interface for Physiological Data: A Systematic Review of Social Biofeedback Systems and Contexts in Human-Computer Interaction
原文标题： Shared User Interfaces of Physiological Data: Systematic Review of Social Biofeedback Systems and Contexts in HCI
Address: http://arxiv.org/abs/2204.00720
By Clara Moge, Katherine Wang, Youngjun Cho
As an emerging interaction paradigm, physiological computing is increasingly used to measure and feed back information about our internal psychophysiological states. While most applications for physiological computing are designed for personal use, recent research has explored how biofeedback can be socially shared among multiple users to enhance communication between people. This paper reviews empirical advances in this area of study, systematically reviewing 64 studies to describe the context and impact of interactions in social biofeedback systems. Our findings highlight the importance of the physiological-temporal and social contextual factors surrounding the sharing of physiological data, and how it promotes social-emotional capacity at three different levels: personal, interpersonal, and task-centric. We also present a framework for social biofeedback interaction to elucidate the current space for physiological-social interaction. We use it to discuss the implications and ethical considerations of future research and design of social biofeedback interfaces.
Based on machine learning, it reveals real-world CO2 reductions and their determinants for ride-sharing
原文标题： Revealing the real-world CO2 emission reduction of ridesplitting and its determinants based on machine learning
Address: http://arxiv.org/abs/2204.00777
作者: Wenxiang Li, Yuanyuan Li, Ziyuan Pu, Long Cheng, Lei Wang, Linchuan Yang
Abstract: Ridesplitting is a form of ride-sharing service that has great potential to mitigate the negative impact of ride-sharing services on the environment. However, most existing studies explore their theoretical environmental benefits based solely on optimization models and simulations. In order to put it into practice, this study aims to reveal the reduction of ride-sharing in the real world and its determinants based on the observational data of ride-sharing services in Chengdu, China. This study combined trip data with copeRT models to calculate CO2 emissions from ride-sharing (carpooling) and their alternative bikes (regular carpooling) to estimate the CO2 reduction per rideshare trip. The results show that not all ride-sharing trips reduce carpooling emissions in the real world. Carpooling's CO2 reduction rate varies by trip, averaging 43.15g/km. Then, an interpretable machine learning model gradient hoist was applied to explore the relationship between carpooling's CO2 reduction rate and its determinants. Based on the SHapley Additive exPlanations method, determining the overlap and detour rates of carpooling is the most important factor in determining the CO2 reduction rate of carpooling. Increasing the overlap rate, the number of shared rides, the average speed and the distance ratio of the ride, and reducing the detour rate, the actual travel distance, and the distance gap between the rides, can improve the CO2 emission reduction rate of carpooling. In addition, the nonlinear effects and interactions of several key factors were examined through partial correlation plots. This study provides a scientific approach for governments and ride-sharing companies to better assess and optimize the environmental benefits of ride-sharing.
Maon? caricature? Characterize spontaneous creative competitions on social media
原文标题： MAANG? MANGA? Characterizing Spontaneous Ideation Contest on Social Media
Address: http://arxiv.org/abs/2204.00910
By Kunihiro Miyazaki, Takayuki Uchiba, Haewoon Kwak, Jisun An
Social media is not only a place for people to communicate about daily affairs, but also a virtual place to convey and exchange various ideas. These ideas are known as the original voices of potential consumers and come from a wide range of people who may not participate in consumer surveys, so their opinions may be of high value to the company. However, how users can share their ideas on social media is still not fully explored. This study investigated a spontaneous contest of ideas about common terminology for new big tech companies that took place when Facebook changed its name to Meta. We built a comprehensive dataset of tweets containing candidates and examined how social media users suggested, disseminated, and exchanged those tweets. Our findings suggest that different ideas are better on different metrics. After the creative contest began, the ranking of ideas was not immediately decided. The first to publish ideas has fewer followers than those who publish them a second time or only share them. We also confirmed that replies accumulate unique ideas, but most are added at the first depth of the reply tree. This research will promote the use of social media as part of the industry's open innovation and co-creation process.
Whose advantage? Measure the attention dynamics of controversial topics on YouTube and Twitter
原文标题： Whose Advantage? Measuring Attention Dynamics across YouTube and Twitter on Controversial Topics
Address: http://arxiv.org/abs/2204.00988
Written by JooYoung Lee, Siqi Wu, Ali Mert Ertugrul, Yu-Ru Lin, Lexing Xie
Ideological asymmetries have recently been observed in the controversial online space, and while liberals are known to have a demographic advantage on digital platforms, the voice of conservatives seems to be relatively more pronounced. However, most previous research has focused on a single platform or a single political theme. Whether an ideological group gets more attention in platforms and themes, and how the focus dynamics evolve over time, has yet to be explored. In this work, we presented a quantitative study that linked collective attention on two social media platforms (YouTube and Twitter) to focus on online activity over a 16-month period around videos of three controversial political topics, including abortion, gun control, and black lives. We present several video-centric metrics to describe how different ideological groups accumulate online attention. We found that neither side had a winning streak: left-leaning videos were generally more viewed and engaging than right-leaning videos, but with fewer tweets. The attention time series of left-leaning videos unfolds faster, but right-leaning videos take longer. Web analysis of early adopters and tweet cascades shows that the spread of information from left-leaning videos tends to involve focused participants; right-leaning videos begin early in the attention lifecycle. Taken together, our findings transcend static images of ideological asymmetry in the digital space and provide a set of ways to quantify attention dynamics on different social platforms.
Aging effects in Schelling separation models
Aging effects in Schelling Segregation model
Address: http://arxiv.org/abs/2204.01417
作者: David Abella, Maxi San Miguel, José J. Ramasco
The Schelling model has become a paradigm in the social sciences to explain the emergence of residential spatial segregation, even with a high tolerance for mixed communities around citizens. In particular, we considered a noise-constrained version of the Schelling model, in which subjects maximize their satisfaction by moving toward an infinite range of movements to satisfy the void, which is related to the composition of the local community. We increase the aging effect by making the probability of the subject move inversely proportional to the time it takes for them to be satisfied at their current position. This mechanism simulates the development of emotional attachment to a position where the subject has been satisfied for a period of time. The introduction of aging has several major effects on the static and dynamics of the model: the phase transition between the separated and mixed phases of the original model disappears, and we observe that the separation state has a high level of subject satisfaction, even for high tolerance values. In addition, the dynamics of the newly separated phases are characterized by slow power-law coarsening processes and glassy dynamics, in which the asymptotic time translation invariance is broken.
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