Sticky prospects: Loss frames are cognitively stickier than gain frames.

Research across numerous domains has highlighted the current--and presumably temporary--effects of frames on preference and behavior. Yet people often encounter information that has been framed in different ways across contexts, and there are reasons to predict that certain frames, once encountered, might tend to stick in the mind and resist subsequent reframing. We propose that loss frames are stickier than gain frames in their ability to shape people's thinking. Specifically, we suggest that the effect of a loss frame may linger longer than that of a gain frame in the face of reframing and that this asymmetry may arise because it is more difficult to convert a loss-framed concept into a gain-framed concept than vice versa. Supporting this notion, loss-to-gain (vs. gain-to-loss) reframing had a muted impact on both risk preferences (Study 1) and evaluation (Study 2). Moreover, participants took longer to solve a math problem that required reconceptualizing losses as gains than vice versa (Studies 3-5), and reframing changed gain-based conceptualizations but not loss-based ones (Study 6). We discuss implications for understanding a key process underlying negativity bias, as well as how sequential frames might impact political behavior and economic recovery

RTextTools: A Supervised Learning Package for Text Classification

Social scientists have long hand-labeled texts to create datasets useful for studying topics from congressional policymaking to media reporting. Many social scientists have begun to incorporate machine learning into their toolkits. RTextTools was designed to make machine learning accessible by providing a start-to-finish product in less than 10 steps. After installing RTextTools, the initial step is to generate a document term matrix. Second, a container object is created, which holds all the objects needed for further analysis. Third, users can use up to nine algorithms to train their data. Fourth, the data are classified. Fifth, the classification is summarized. Sixth, functions are available for performance evaluation. Seventh, ensemble agreement is conducted. Eighth, users can cross-validate their data. Finally, users write their data to a spreadsheet, allowing for further manual coding if required

Sticky prospects: loss frames are cognitively stickier than gain frames.

Research across numerous domains has highlighted the current--and presumably temporary--effects of frames on preference and behavior. Yet people often encounter information that has been framed in different ways across contexts, and there are reasons to predict that certain frames, once encountered, might tend to stick in the mind and resist subsequent reframing. We propose that loss frames are stickier than gain frames in their ability to shape people's thinking. Specifically, we suggest that the effect of a loss frame may linger longer than that of a gain frame in the face of reframing and that this asymmetry may arise because it is more difficult to convert a loss-framed concept into a gain-framed concept than vice versa. Supporting this notion, loss-to-gain (vs. gain-to-loss) reframing had a muted impact on both risk preferences (Study 1) and evaluation (Study 2). Moreover, participants took longer to solve a math problem that required reconceptualizing losses as gains than vice versa (Studies 3-5), and reframing changed gain-based conceptualizations but not loss-based ones (Study 6). We discuss implications for understanding a key process underlying negativity bias, as well as how sequential frames might impact political behavior and economic recovery

Sticky prospects: loss frames are cognitively stickier than gain frames.

Research across numerous domains has highlighted the current--and presumably temporary--effects of frames on preference and behavior. Yet people often encounter information that has been framed in different ways across contexts, and there are reasons to predict that certain frames, once encountered, might tend to stick in the mind and resist subsequent reframing. We propose that loss frames are stickier than gain frames in their ability to shape people's thinking. Specifically, we suggest that the effect of a loss frame may linger longer than that of a gain frame in the face of reframing and that this asymmetry may arise because it is more difficult to convert a loss-framed concept into a gain-framed concept than vice versa. Supporting this notion, loss-to-gain (vs. gain-to-loss) reframing had a muted impact on both risk preferences (Study 1) and evaluation (Study 2). Moreover, participants took longer to solve a math problem that required reconceptualizing losses as gains than vice versa (Studies 3-5), and reframing changed gain-based conceptualizations but not loss-based ones (Study 6). We discuss implications for understanding a key process underlying negativity bias, as well as how sequential frames might impact political behavior and economic recovery

Vol. 18(1)- Replication Data for: When Celebrity and Political Journalism Collide: Reporting Standards, Entertainment, and the Conundrum of Covering Donald Trump's 2016 Campaign

Readme (.txt), data (.dta), and command (.do) files to replicate our paper, "When Celebrity and Political Journalism Collide: Reporting Standards, Entertainment, and the Conundrum of Covering Donald Trump's 2016 Campaign" Please contact us with any questions

The conditional nature of presidential agenda influence on TV news : The case of education

The president's ability to influence media attention is crucial to theoretical understandings of institutional agenda setting. We add a key caveat: The conditional nature of how presidential attention influences media attention to a given issue. We highlight two conditioning variables: the president's party and the degree of public concern for the issue. Presidential influence on media is enhanced when his or her party "owns" the issue. But since public concern about an issue tends to prompt saturated media coverage, strong public concern mitigates presidential influence on the media. We test these ideas by examining presidential and television attention to education, 1974-2007. Using time-series models, we find support for our hypotheses, with implications for political communication research and applied political strategy

Computational Tool for Gas Flow Modeling through the Piston Assembly

The main topic of this bachelor’s thesis is to create a graphical users interface (GUI) in Matlab, facilitating the entry of input parameters for the calculation of the gas flow through the piston assembly and its evaluation. The first part is dedicated to the theory of piston rings followed by an introduction into the gas flow problematics. The second part concerns the procedure of creating the aforementioned GUI