Coming Out, Entertainment Television, and the Youth Revolt

2018 ◽  
pp. 148-177
Author(s):  
Jeremiah J. Garretson
Keyword(s):  
Public Opinion ◽  
Attitude Change ◽  
Coming Out ◽  
Millennial Generation ◽  
Direct Contact ◽  
Data Sets ◽  
Distinctive Features ◽  
Two Factors ◽  
Entertainment Television ◽  
Rights Issues

This chapter begins by describing the dramatic increase in direct contact of the American public with LGBTQ people documented using polling data. Trends in depictions of LGBTQ people on television and film are outlined, which mirror the expansion of direct contact with LGBTQs. These two factors---direct contact and meditated contact---are processed in similar ways psychologically according to affective liberalization. Both are predicted to be more effective at attitude change among younger people. The theory is then empirically tested using four different expansive cross-time public opinion datasets. All four analyses of the data-sets come to same conclusion, contact with LGBTQs (mediated and interpersonal) explains all the distinctive features of attitude change---its large magnitude, its timing, its broadness across specific gay rights issues, and its concentration among the millennial generation.

A Transformed Society

2018 ◽  
pp. 3-33
Author(s):  
Jeremiah J. Garretson
Keyword(s):  
Public Opinion ◽  
Social Change ◽  
Attitude Change ◽  
Lgbt Rights ◽  
Public Opinion Research ◽  
Distinctive Features ◽  
Mass Attitudes ◽  
Rights Issues

The introductory chapter first outlines the basic puzzle that the book will focus on explaining: Why have mass attitudes involving lesbians and gays changed so radically since the early 1990s when public opinion research has shown that the public’s views on most issues are generally stable? The contours of attitude change on LGBT rights issues across time are then surveyed. The central theory of the book---Affective Liberalization---is then described. Lastly, the primary distinctive features of the book, including its emphasis on LGBTQ people as a primary mover of social change, is discussed. The chapter ends with a brief summary of the book.

Public Opinion and Violence Against Foreigners in the Reunified Germany

1994 ◽  
Vol 23 (3) ◽  
Author(s):  
Thomas Ohlemacher
Keyword(s):  
Public Opinion ◽  
Empirical Analysis ◽  
Data Sets ◽  
Theoretical Terms ◽  
Positive Correlation ◽  
Two Factors ◽  
The Media ◽  
The Empirical Analysis ◽  
Opinion Polls ◽  
Violent Events

AbstractThe reunified Germany has faced an increasing incidence of violence against foreigners. The study presented here focuses on the interrelationship between public opinion (measured in opinion polls) and the number of violent attacks (counted by the German Federal Police). The empirical analysis detects a positive correlation between the two factors. This correlation was to be expected in theoretical terms. Violent events, widely covered by the media, are important for both data sets. Xenophobic riots like Hoyerswerda and Rostock support critical comments and an increase in violence, whereas the murders of Mölln support a decrease in both. Specific forms and quantities of violence seem to enable people to communicate a critical opinion towards foreigners and thereby stimulate renewed violence. However, “too much” violence builds up a new latency of communication, which decreases violence once more.

Trust in the Police: Cross-country Comparisons

2012 ◽  
pp. 24-47
Author(s):  
V. Gimpelson ◽  
G. Monusova
Keyword(s):  
Public Opinion ◽  
Public Attitudes ◽  
Crime Rates ◽  
Authoritarian Regimes ◽  
Data Sets ◽  
The Public ◽  
Positive Attitudes ◽  
Cross Country ◽  
Police Activity

Using different cross-country data sets and simple econometric techniques we study public attitudes towards the police. More positive attitudes are more likely to emerge in the countries that have better functioning democratic institutions, less prone to corruption but enjoy more transparent and accountable police activity. This has a stronger impact on the public opinion (trust and attitudes) than objective crime rates or density of policemen. Citizens tend to trust more in those (policemen) with whom they share common values and can have some control over. The latter is a function of democracy. In authoritarian countries — “police states” — this tendency may not work directly. When we move from semi-authoritarian countries to openly authoritarian ones the trust in the police measured by surveys can also rise. As a result, the trust appears to be U-shaped along the quality of government axis. This phenomenon can be explained with two simple facts. First, publicly spread information concerning police activity in authoritarian countries is strongly controlled; second, the police itself is better controlled by authoritarian regimes which are afraid of dangerous (for them) erosion of this institution.

Inside Trending Topic Algorithm: How Do Human Interactions Drive Public Opinion in an Artificial Environment

2021 ◽  
pp. 089443932110415
Author(s):  
Vanessa Russo ◽  
Emiliano del Gobbo
Keyword(s):  
Public Opinion ◽  
Semantic Network ◽  
Opinion Leader ◽  
Computational Techniques ◽  
Data Sets ◽  
Process Data ◽  
Data Set ◽  
Social Actors ◽  
Human Interactions ◽  
Artificial Environment

The object of this research is to exploit the algorithm of Twitter’s trending topic (TT) and identify the elements capable of guiding public opinion in the Italian panorama. The underlying hypotheses that guide the whole article, confirmed by the research results, concern the existence of (a) a limited number of elements at the base of each popular hashtag with very high viral power and (b) hashtags transversal to the themes detected by the Twitter algorithm that define specific opinion polls. Through computational techniques, it was possible to extract and process data sets from six specific hashtags highlighted by TT. In a first step through social network analysis, we analyzed the hashtag semantic network to identify the hashtags transversal to the six TTs. Subsequently, we selected for each data set the contents with high sharing power and created a “potential opinion leader” index to identify users with influencer characteristics. Finally, a cross section of social actors able to guide public opinion in the Twittersphere emerged from the intersection between potentially influential users and the viral contents.

PEMILIHAN KARIR PADA PEGAWAI GENERASI MILLENIAL (STUDI KASUS : PEGAWAI PT XYZ)

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
FEBRU RADHIANJAYA
Keyword(s):  
Qualitative Research ◽  
Human Resources ◽  
Career Choice ◽  
Millennial Generation ◽  
Career Selection ◽  
Interview Method ◽  
Dominating Number ◽  
Two Factors ◽  
A Company

PT XYZ is a company engaged in the field of production and services that has Human Resources spread throughout Indonesia. In this study, the object of observation is the employee in the East Java Unit which has a total of 2,300 personnel with the composition of the Millennial Generation (born 1981-1994) of 51% as the dominating number of employees in PT XYZ. The results of an interest survey conducted on 698 structural employees at the Basic Supervisor level (managerial type career) at PT XYZ East Java Unit, showed that 25% or 171 employees of the millennial generation chose functional careers (type of expertise). This phenomenon is then explored further in the research objectives, namely what factors influence career selection in millennial generation employees. This research is a qualitative research that uses the interview method. The result is that there are two factors that influence career choice, namely responsibility and type of work.   Keywords : Millenials, Careers, Qualitative

scholarly journals Surface-Related Features Responsible for Cytotoxic Behavior of MXenes Layered Materials Predicted with Machine Learning Approach

Materials ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3083
Author(s):  
Maciej E. Marchwiany ◽  
Magdalena Birowska ◽  
Mariusz Popielski ◽  
Jacek A. Majewski ◽  
Agnieszka M. Jastrzębska
Keyword(s):  
Machine Learning ◽  
Transition Metal Oxides ◽  
2D Materials ◽  
Experimental Studies ◽  
Biological Data ◽  
Data Sets ◽  
Toxicological Studies ◽  
Two Factors ◽  
Health Need

To speed up the implementation of the two-dimensional materials in the development of potential biomedical applications, the toxicological aspects toward human health need to be addressed. Due to time-consuming and expensive analysis, only part of the continuously expanding family of 2D materials can be tested in vitro. The machine learning methods can be used—by extracting new insights from available biological data sets, and provide further guidance for experimental studies. This study identifies the most relevant highly surface-specific features that might be responsible for cytotoxic behavior of 2D materials, especially MXenes. In particular, two factors, namely, the presence of transition metal oxides and lithium atoms on the surface, are identified as cytotoxicity-generating features. The developed machine learning model succeeds in predicting toxicity for other 2D MXenes, previously not tested in vitro, and hence, is able to complement the existing knowledge coming from in vitro studies. Thus, we claim that it might be one of the solutions for reducing the number of toxicological studies needed, and allows for minimizing failures in future biological applications.

scholarly journals Radar Emission Sources Identification Based on Hierarchical Agglomerative Clustering for Large Data Sets

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Janusz Dudczyk
Keyword(s):  
Clustering Algorithm ◽  
Large Data ◽  
Large Data Sets ◽  
Emission Sources ◽  
Data Sets ◽  
Agglomerative Clustering ◽  
Distinctive Features ◽  
Identification Process ◽  
Hierarchical Agglomerative Clustering ◽  
Repetition Interval

More advanced recognition methods, which may recognize particular copies of radars of the same type, are called identification. The identification process of radar devices is a more specialized task which requires methods based on the analysis of distinctive features. These features are distinguished from the signals coming from the identified devices. Such a process is called Specific Emitter Identification (SEI). The identification of radar emission sources with the use of classic techniques based on the statistical analysis of basic measurable parameters of a signal such as Radio Frequency, Amplitude, Pulse Width, or Pulse Repetition Interval is not sufficient for SEI problems. This paper presents the method of hierarchical data clustering which is used in the process of radar identification. The Hierarchical Agglomerative Clustering Algorithm (HACA) based on Generalized Agglomerative Scheme (GAS) implemented and used in the research method is parameterized; therefore, it is possible to compare the results. The results of clustering are presented in dendrograms in this paper. The received results of grouping and identification based on HACA are compared with other SEI methods in order to assess the degree of their usefulness and effectiveness for systems of ESM/ELINT class.

Critical Events and Attitude Change: Support for Gun Control After Mass Shootings

2018 ◽  
Vol 7 (04) ◽  
pp. 903-911 ◽  
Author(s):  
Jon C. Rogowski ◽  
Patrick D. Tucker
Keyword(s):  
Public Opinion ◽  
Attitude Change ◽  
Public Policies ◽  
Gun Control ◽  
Critical Events ◽  
Cross Sectional ◽  
Political Opportunities ◽  
Nationally Representative ◽  
Sandy Hook Elementary School ◽  
Sandy Hook

When and to what extent do crises and significant events induce changes in political attitudes? Theories of public opinion and policymaking predict that major events restructure public opinion and pry open new political opportunities. We examine the effect of major events on support for public policies in the context of the Sandy Hook Elementary School mass shooting in December 2012 using a nationally representative panel survey of US adults. Across both cross-sectional and within-subject analyses, we find no evidence that Americans granted greater support for gun control after the Sandy Hook shooting. Our null findings persist across a range of political and demographic groups. We also find no evidence of attitude polarization as a result of Sandy Hook. Our results suggest that elite polarization in a particular issue area leads citizens to employ motivated reasoning when interpreting critical events, thereby reducing the capacity for attitude change. Our findings have important implications for identifying the conditions under which major events affect support for public policies and create political opportunities for policy change.

Religious Elites and Public Opinion: The Impact of the Bishops' Peace Pastoral

1992 ◽  
Vol 54 (1) ◽  
pp. 112-143 ◽  
Author(s):  
Kenneth D. Wald
Keyword(s):  
Public Opinion ◽  
Attitude Change ◽  
Military Spending ◽  
Arms Race ◽  
Persuasive Communication ◽  
War And Peace ◽  
Pastoral Letter ◽  
The Many ◽  
The Impact ◽  
Catholic Bishops

In their 1983 pastoral letter on war and peace, the Catholic bishops attempted to sway American public opinion against the arms race. Polling data suggest that The Challenge of Peace stimulated a sharp but short-lived reaction against military spending among American Catholics. The message was best received by Catholics strongly tied to their church, reversing a historical correlation between religiosity and nationalism. The pastoral must be judged relatively successful in its mission, particularly in light of the many barriers to attitude change. Greater sensitivity to those obstacles could enhance the success of future efforts at persuasive communication by church authorities.

Political Ideology and Issue Importance

2020 ◽  
pp. 106591292096774
Author(s):  
Douglas Rice ◽  
Brian F. Schaffner ◽  
David J. Barney
Keyword(s):  
Public Opinion ◽  
Political Ideology ◽  
Latent Variable ◽  
Past Research ◽  
Data Sets ◽  
Issue Salience ◽  
Individual Level ◽  
Measurement Models ◽  
The Individual ◽  
Issue Importance

Past research has shown that issues vary significantly in their salience across citizens, explaining key outcomes in political behavior. Yet it remains unclear how individual-level differences in issue salience affect the measurement of latent constructs in public opinion, namely political ideology. In this paper, we test whether scaling approaches that fail to incorporate individual-level differences in issue salience could understate the predictive power of ideology in public opinion research. To systematically examine this assertion, we employ a series of latent variable models which incorporate both issue importance and issue position. We compare the results of these different and diverse scaling approaches to two survey data sets, investigating the implications of accounting for issue salience in constructing latent measures of ideology. Ultimately, we find that accounting for issue importance adds little information to a more basic approach that uses only issue positions, suggesting ideological signals for measurement models reside most prominently in the issue positions of individuals rather than the importance of those issues to the individual.

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