The consequences of online partisan media.

What role do ideologically extreme media play in the polarization of society? Here we report results from a randomized longitudinal field experiment embedded in a nationally representative online panel survey (N = 1,037) in which participants were incentivized to change their browser default settings and social media following patterns, boosting the likelihood of encountering news with either a left-leaning (HuffPost) or right-leaning (Fox News) slant during the 2018 US midterm election campaign. Data on ≈ 19 million web visits by respondents indicate that resulting changes in news consumption persisted for at least 8 wk. Greater exposure to partisan news can cause immediate but short-lived increases in website visits and knowledge of recent events. After adjusting for multiple comparisons, however, we find little evidence of a direct impact on opinions or affect. Still, results from later survey waves suggest that both treatments produce a lasting and meaningful decrease in trust in the mainstream media up to 1 y later. Consistent with the minimal-effects tradition, direct consequences of online partisan media are limited, although our findings raise questions about the possibility of subtle, cumulative dynamics. The combination of experimentation and computational social science techniques illustrates a powerful approach for studying the long-term consequences of exposure to partisan news.

Effects of Sensing Tactile Arrays, Shear Force, and Proprioception of Robot on Texture Recognition.

In robotics, tactile perception is important for fine control using robot grippers and hands. To effectively incorporate tactile perception in robots, it is essential to understand how humans use mechanoreceptors and proprioceptors to perceive texture. Thus, our study aimed to investigate the impact of tactile sensor arrays, shear force, and the positional information of the robot's end effector on its ability to recognize texture. A deep learning network was employed to classify tactile data from 24 different textures that were explored by a robot. The input values of the deep learning network were modified based on variations in the number of channels of the tactile signal, the arrangement of the tactile sensor, the presence or absence of shear force, and the positional information of the robot. By comparing the accuracy of texture recognition, our analysis revealed that tactile sensor arrays more accurately recognized the texture compared to a single tactile sensor. The utilization of shear force and positional information of the robot resulted in an improved accuracy of texture recognition when using a single tactile sensor. Furthermore, an equal number of sensors placed in a vertical arrangement led to a more accurate distinction of textures during exploration when compared to sensors placed in a horizontal arrangement. The results of this study indicate that the implementation of a tactile sensor array should be prioritized over a single sensor for enhanced accuracy in tactile sensing, and the use of integrated data should be considered for single tactile sensing.

The Exploration of How Social Media Cultivate College Student Smokers: Theorizing Valence of Communication, Impression Management, and Perceived Risks and Benefits of Smoking in the O1-S-R1-O2-R2 Model.

The purpose of this study is to build a theoretical framework to account for how social media lead college students to smoke. Arguing critical concepts, such as valence of communication, impression management, perceived risks and benefits, this study develops the O 1 -S-R 1 -O 2 -R 2 model. For this, we test a separated model for smokers and nonsmokers. For smokers, the effect of exposure to pro-smoking content on smoking behavior is mediated by an impression of smokers, a favorable expression about smoking, and perceived benefits. And, the effect of exposure to anti-smoking content on smoking behavior is mediated by an unfavorable expression about smoking and perceived risks. However, such mediation processes cannot be observed for nonsmokers; namely, the effect of exposure to pro-smoking content on smoking intention is only mediated by a favorable expression about smoking. Considering the separated path models for smokers and nonsmokers, theoretical and practical implications are suggested for future study. Methodological limitations are discussed as well.

The Effects of Expressing Religious Support Online for Breast Cancer Patients.

The growth of online support groups has led to an expression effects paradigm within the health communication literature. Although religious support expression is characterized as a typical subdimension of emotional support, we argue that in the context of a life-threatening illness, the inclusion of a religious component creates a unique communication process. Using data from an online group for women with breast cancer, we test a theoretical expression effects model. Results demonstrate that for breast cancer patients, religious support expression has distinct effects from general emotional support messages, which highlights the need to further theorize expression effects along these lines.

Coordination patterns reveal online political astroturfing across the world.

Online political astroturfing-hidden information campaigns in which a political actor mimics genuine citizen behavior by incentivizing agents to spread information online-has become prevalent on social media. Such inauthentic information campaigns threaten to undermine the Internet's promise to more equitable participation in public debates. We argue that the logic of social behavior within the campaign bureaucracy and principal-agent problems lead to detectable activity patterns among the campaign's social media accounts. Our analysis uses a network-based methodology to identify such coordination patterns in all campaigns contained in the largest publicly available database on astroturfing published by Twitter. On average, 74% of the involved accounts in each campaign engaged in a simple form of coordination that we call co-tweeting and co-retweeting. Comparing the astroturfing accounts to various systematically constructed comparison samples, we show that the same behavior is negligible among the accounts of regular users that the campaigns try to mimic. As its main substantive contribution, the paper demonstrates that online political astroturfing consistently leaves similar traces of coordination, even across diverse political and country contexts and different time periods. The presented methodology is a reliable first step for detecting astroturfing campaigns.

Do Online Voter Guides Empower Citizens?: Evidence from a Field Experiment with Digital Trace Data.

Voting Advice Applications (VAAs), which provide citizens with information on the party that best represents their political preferences, are often cited as evidence of the empowering capabilities of digital tools. Aside from the informational benefits of these voter guides, observational studies have suggested a strong effect on political participation and vote choice. However, existing impact evaluations have been limited by a reliance on convenience samples, lack of random assignment, or both. This raises questions about self-selection and the precise mechanisms underlying how voters learn about politics. Here, we provide evidence from a field experiment with survey outcomes conducted with a sample of over 1,000 German citizens in the 2017 federal election campaign. Using linked panel survey and digital trace data combined with a randomized encouragement to complete a VAA, we assess respondents' compliance with treatment and observe how the use of this tool affects political behavior, attitudes, media consumption, political knowledge, and even social media activity. Our findings reveal that the overwhelming consensus in favor of positive effects on turnout and vote choice should be treated with caution, as we find no such effects. Rather, the actual virtue of VAAs in a complex online information environment lies in increasing knowledge about parties' positions on issues-exactly the kind of information these tools were designed to provide.

New amorphous hole blocking materials for high efficiency OLEDs.

Two new amorphous molecular materials, 2,5-bis(2',5'-dimethyl-4-triphenylsilyl-phenyl)-[1,3,4]oxadiazole (BDTSO) and 2,5-bis(2',5'-dimethyl-4-triphenylsilyl-phenyl)-[1,3,4]thiadiazole (BDTST) were synthesized and investigated as hole blocking materials (HBM) for organic light-emitting diodes. The efficiency of electroluminescent device was improved by using BDTSO instead of BAlq. The current and power efficiency of the device using BDTSO as HBM is 39.6 cd/A and 13.1 lm/W at 10 mA/cm2, respectively, which is higher compared to the same values for devices using BDTST and BAq which are typically used as HBM.

How social media influence college students' smoking attitudes and intentions.

Building on the influence of presumed influence (IPI) model, this study examines how smoking- related messages on social media influence college students' smoking. We surveyed 366 college students from three U.S. Midwestern universities in 2012 and examined the effects of expression and reception of smoking-related messages on smoking using path analysis. We found that the expression and reception of prosmoking messages not only directly affected smoking but also had indirect effects on smoking through (1) perceived peer expression of prosmoking messages and (2) perceived peer smoking norms. For antismoking messages, only reception had a significant indirect influence on smoking through (1) perceived peer reception of antismoking messages and (2) perceived peer smoking norms. In conclusion, social media function as an effective communication channel for generating, sharing, receiving, and commenting on smoking-related content and are thus influential on college students' smoking.

Predictors of the change in the expression of emotional support within an online breast cancer support group: a longitudinal study.

OBJECTIVES: To explore how the expression of emotional support in an online breast cancer support group changes over time, and what factors predict this pattern of change. METHODS: We conducted growth curve modeling with data collected from 192 participants in an online breast cancer support group within the Comprehensive Health Enhancement Support System (CHESS) during a 24-week intervention period. RESULTS: Individual expression of emotional support tends to increase over time for the first 12 weeks of the intervention, but then decrease slightly with time after that. In addition, we found that age, living situation, comfort level with computer and the Internet, coping strategies were important factors in predicting the changing pattern of expressing emotional support. CONCLUSIONS: Expressing emotional support changed in a quadratic trajectory, with a range of factors predicting the changing pattern of expression. PRACTICAL IMPLICATIONS: These results can provide important information for e-health researchers and physicians in determining the benefits individuals can gain from participation in should CMSS groups as the purpose of cancer treatment.