Trump, Twitter, and news media responsiveness: a media systems approach

How populists engage with media of various types, and are treated by those media, are questions of international interest. In the United States, Donald Trump stands out for both his populism-inflected campaign style and his success at attracting media attention. This article examines how interactions between candidate communications, social media, partisan media, and news media combined to shape attention to Trump, Clinton, Cruz, and Sanders during the 2015–2016 American presidential primary elections. We identify six major components of the American media system and measure candidates’ efforts to gain attention from them. Our results demonstrate that social media activity, in the form of retweets of candidate posts, provided a significant boost to news media coverage of Trump, but no comparable boost for other candidates. Furthermore, Trump tweeted more at times when he had recently garnered less of a relative advantage in news attention, suggesting he strategically used Twitter to trigger coverage.Accepted manuscrip

Offline Social Relationships and Online Cancer Communication: Effects of Social and Family Support on Online Social Network Building

This study investigates how social support and family relationship perceptions influence breast cancer patients’ online communication networks in a computer-mediated social support (CMSS) group. To examine social interactions in the CMSS group, we identified two types of online social networks: open and targeted communication networks. The open communication network reflects group communication behaviors (i.e., one-to-many or “broadcast” communication) in which the intended audience is not specified; in contrast, the targeted communication network reflects interpersonal discourses (i.e., one-to-one or directed communication) in which the audience for the message is specified. The communication networks were constructed by tracking CMSS group usage data of 237 breast cancer patients who participated in one of two National Cancer Institute-funded randomized clinical trials. Eligible subjects were within 2 months of a diagnosis of primary breast cancer or recurrence at the time of recruitment. Findings reveal that breast cancer patients who perceived less availability of offline social support had a larger social network size in the open communication network. In contrast, those who perceived less family cohesion had a larger targeted communication network in the CMSS group, meaning they were inclined to use the CMSS group for developing interpersonal relationships

#Politics on Twitter goes beyond the left-right ideology divide

In U.S. politics, the main narrative tends to manifest as left vs right, Democrat vs. Republican, but is this reflected in the social media sphere as well? In new research which maps how hashtags in political tweets were used in the lead up to the 2010 Congressional midterm elections, Leticia Bode, Alex Hanna, JungHwan Yang, and Dhavan V. Shah found that some hashtags occurred in discussion groups that were there ideological opposite. They write that this ‘hashjacking’ was a way in which conservatives were able to enter and disrupt a more liberal community’s online discussion

Mapping the Political Twitterverse: Finding Connections Between Political Elites

Twitter provides a new and important tool for politicalactors, and is increasingly being used as such. In the2010 midterm elections, the vast majority of candidates forthe U.S. House of Representatives and virtually all candidatesfor U.S. Senate and governorships used Twitter toreach out to potential supporters, direct them to particularpieces of information, request campaign contributions, andmobilize their political action. Despite the level of activity,we have little understanding of what the political Twitterverselooks like in terms of communication and discourse.This project seeks to remedy that lack of understandingby mapping candidates for federal office in 2010 and theirfollowers, according to their use of the 4016 most used hashtags(keywords). Our data set is uniquely constructed fromtweets of most of the candidates running for the U.S. Houseof Representatives in 2010, all the candidates for the Senateand governorships, and a random sample of their followers.From this we utilize multidimensional scaling to constructa visual map based on hashtag usage. We find that ourdata have both local and global interpretations that reflectnot only political leaning but also strategies of communication.This study provides insight into innovation in newmedia usage in political behavior, as well as a snapshot ofthe political twitterverse in 2010

A Smartphone-Based Support Group for Alcoholism: Effects of Giving and Receiving Emotional Support on Coping Self-Efficacy and Risky Drinking

The purpose of this study was to investigate the nature and effects of exchanging emotional support via a smartphone-based support group for patients with alcohol dependence. Of the 349 patients who met the Diagnostic and Statistical Manual of Mental Disorders (4th ed.) criteria for alcohol dependence, 153 patients participated in the discussion group within the Addiction-Comprehensive Health Enhancement Support System, a smartphone application aimed at reducing relapse. This was developed to prevent problem drinking by offering individuals in recovery for alcohol dependence automated 24/7 recovery support services and frequent assessment of their symptom status as part of their addiction care. The results showed that receiving emotional support from health care providers improved coping self-efficacy. Giving emotional support and receiving emotional support from health care providers acted as a buffer, protecting patients from the harmful effects of emotional distress on risky drinking. Clinicians and researchers should use the features of smartphone-based support groups to reach out to alcoholic patients in need and encourage them to participate in the exchange of emotional support with others

Evaluating measures of campaign advertising exposure on political learning

Scholars employ various methods to measure exposure to televised political advertising but often arrive at conflicting conclusions about its impact on the thoughts and actions of citizens. We attempt to clarify one of these debates while validating a parsimonious measure of political advertising exposure. To do so, we assess the predictive power of six different measurement approaches - from the simple to the complex - on learning about political candidates. Two datasets are used in this inquiry: (1) geo-coded political advertising time-buy data, and (2) a national panel study concerning patterns of media consumption and levels of political knowledge. We conclude that many traditional methods of assessing exposure are flawed. Fortunately, there is a relatively simple measure that predicts knowledge about information featured in ads. This measure involves combining a tally of the volume of advertisements aired in a market with a small number of survey questions about the television viewing habits of geo-coded respondents

Expression and Reception: An Analytic Method for Assessing Message Production and Consumption in CMC

This article presents an innovative methodology to study computer-mediated communication (CMC), which allows analysis of the multi-layered effects of online expression and reception. The methodology is demonstrated by combining the following three data sets collected from a widely tested eHealth system, the Comprehensive Health Enhancement Support System (CHESS): (1) a flexible and precise computer-aided content analysis; (2) a record of individual message posting and reading; and (3) longitudinal survey data. Further, this article discusses how the resulting data can be applied to online social network analysis and demonstrates how to construct two distinct types of online social networks—open and targeted communication networks—for different types of content embedded in social networks

The Wisdom of Partisan Crowds: Comparing Collective Intelligence in Humans and LLM-based Agents

Human groups are able to converge on more accurate beliefs through deliberation, even in the presence of polarization and partisan bias -- a phenomenon known as the "wisdom of partisan crowds." Generated agents powered by Large Language Models (LLMs) are increasingly used to simulate human collective behavior, yet few benchmarks exist for evaluating their dynamics against the behavior of human groups. In this paper, we examine the extent to which the wisdom of partisan crowds emerges in groups of LLM-based agents that are prompted to role-play as partisan personas (e.g., Democrat or Republican). We find that they not only display human-like partisan biases, but also converge to more accurate beliefs through deliberation as humans do. We then identify several factors that interfere with convergence, including the use of chain-of-thought prompt and lack of details in personas. Conversely, fine-tuning on human data appears to enhance convergence. These findings show the potential and limitations of LLM-based agents as a model of human collective intelligence

Design and Evaluation of Tumor‐Specific Dendrimer Epigenetic Therapeutics

Histone deacetylase inhibitors (HDACi) are promising therapeutics for cancer. HDACi alter the epigenetic state of tumors and provide a unique approach to treat cancer. Although studies with HDACi have shown promise in some cancers, variable efficacy and off‐target effects have limited their use. To overcome some of the challenges of traditional HDACi, we sought to use a tumor‐specific dendrimer scaffold to deliver HDACi directly to cancer cells. Here we report the design and evaluation of tumor‐specific dendrimer–HDACi conjugates. The HDACi was conjugated to the dendrimer using an ester linkage through its hydroxamic acid group, inactivating the HDACi until it is released from the dendrimer. Using a cancer cell model, we demonstrate the functionality of the tumor‐specific dendrimer–HDACi conjugates. Furthermore, we demonstrate that unlike traditional HDACi, dendrimer–HDACi conjugates do not affect tumor‐associated macrophages, a recently recognized mechanism through which drug resistance emerges. We anticipate that this new class of cell‐specific epigenetic therapeutics will have tremendous potential in the treatment of cancer.Targeting tumors via epigenetics: Histone deacetylase inhibitors (HDACi) alter the epigenetic state of tumors and are promising therapeutics for cancer. Although studies with HDACi have shown promise in some cancers, variable efficacy and off‐target effects have limited their use. Here we report the design and evaluation of a tumor‐specific dendrimer–HDACi.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111996/1/open201402141.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111996/2/open201402141-sup-0001-misc_information.pd

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