scholarly journals Disappearing Errors in a Conversion Model

2021 ◽  
pp. 341-358
Author(s):  
David P. Fan
Keyword(s):  
Public Opinion ◽  
Diffusion Of Innovations ◽  
Measurement Errors ◽  
Equation Model ◽  
Bad News ◽  
Time Dependent ◽  
Bass Model ◽  
Persuasive Messages ◽  
Conversion Model ◽  
Basic Differential Equation

The same basic differential equation model has been adapted for time-dependent conversions of members of a population among different states. The conversion model has been applied in different contexts such as epidemiological infections, the Bass model for the diffusion of innovations, and the ideodynamic model for public opinion. For example, the ideodynamic version of the model predicts changes in public opinions in response to persuasive messages extending back to an indefinite past. All messages are measured with error, and this chapter discusses how errors in message measurements disappear with time so that predicted opinion values gradually become unaffected by past measurement errors. Prediction uncertainty is discussed using formal statistics, sensitivity analysis, and bootstrap variance calculations. This chapter presents ideodynamic predictions for opinion time series about the Toyota car manufacturer calculated from daily Twitter scores over two-and-a-half years. During this time, there was a sudden onslaught of bad news for Toyota, and the model was able to accurately predict the accompanying drop in favourable public opinion towards Toyota and rise in unfavourable opinion.

scholarly journals Study of measurement errors of Cabinet Office opinion survey

Impact ◽  
2021 ◽  
Vol 2021 (2) ◽  
pp. 6-7
Author(s):  
Harumasa Yoshimura
Keyword(s):  
Public Opinion ◽  
Measurement Errors ◽  
Japanese Society ◽  
Social Research ◽  
Sampling Error ◽  
Opinion Survey ◽  
Community Surveys ◽  
Public Opinion Surveys ◽  
Survey Results ◽  
Negative Impacts

Public opinion surveys are important for gauging the feelings and behaviours of societies. However, there is the possibility of error, which means that the data collected may not accurately reflect the thoughts and opinions of society, which can have dangerous repercussions. In order to minimise such error, with a specific focus on the Japanese Government's Cabinet Office public opinion survey, Professor Harumasa Yoshimura, Nara University, Japan, is investigating measurement error and, in doing so, he hopes to more accurately reflect the true opinions of Japanese society. This research involves integrating the different factors that can affect the reliability of survey results and looking at non-sampling error, which refers to human mistakes. Yoshimura is proposing a new style of social research that integrates psychometric research with sociological community surveys and believes this is the key to enhancing the reliability of public opinion surveys. Ultimately, improving the accuracy of public opinion surveys will have far-reaching benefits that include more accurately depicting thoughts and behaviours and therefore improving awareness of Japanese society, as well as preventing the negative impacts that inaccurate opinion survey results can have, including the political utilisation of academic endeavours.

scholarly journals Modeling the Diffusion of Private Pension Provision

2018 ◽  
Vol 65 (4) ◽  
pp. 385-405
Author(s):  
Larysa Yakymova
Keyword(s):  
Diffusion Of Innovations ◽  
Historical Data ◽  
Pension Funds ◽  
Diffusion Models ◽  
Private Pension ◽  
Bass Model ◽  
Pension Systems ◽  
Pension Schemes ◽  
Diffusion Parameters ◽  
Innovation Diffusion Models

Abstract The purpose of this paper is threefold: to adapt the innovation diffusion models to describe and predict the diffusion of private pension provision; to evaluate the suitability of diffusion models based on the historical data from the Romanian and Ukrainian voluntary pension systems; and to compare the diffusion parameters of private pension provision in these countries. The study proven that diffusion models, such as the Rogers model and the Bass model, can reproduce the diffusion of innovations in the field of pensions. The Rogers diffusion parameters for Romania and Ukraine are almost identical; this gives grounds for a conclusion about the similar behavioral patterns in post-socialist countries. However, some limitations on models use are noted. During the crisis and when using the nudge mechanism, models are not always well-fitting, but when new pension schemes are introduced or new pension funds are opened, models can be used in “guessing by analogy”.

scholarly journals A SYSTEMATIC REVIEW OF STRUCTURAL EQUATION MODEL (SEM)

2020 ◽  
Vol 1 (2) ◽  
pp. 27-39
Author(s):  
H. O. Owolabi ◽  
J. K. Ayandele ◽  
D. D. Olaoye
Keyword(s):  
Structural Equation Model ◽  
Measurement Errors ◽  
Structural Equation ◽  
Statistical Technique ◽  
Equation Model ◽  
Equation Modeling ◽  
Weak Assumption ◽  
Multivariate Statistical ◽  
Software Packages ◽  
Complex Relationships

Structural Equation Model (SEM) is a multivariate statistical technique that has been explored to test relationships between variables. The use of SEM to analyze relationship between variables is premised on the weak assumption of path analysis, regression analysis and so on; that variables are measured without error. This review thus sheds light on the meaning of SEM, its assumptions, steps and some of the terms used in SEM. The importance of item parcelling to SEM and its methods were briefly examined. It also dealt on the stages involved in SEM, similarities and differences between SEM and conventional statistical methods, software packages that can be used for SEM. This article employed systematic literature review method because it critically synthesized research studies and findings on structural equation modeling (SEM). It could be concluded that SEM is useful in analyzing a set of relationships between variables using diagrams. SEM can also be useful in minimizing measurement errors and in enhancing reliability of constructs. Based on this, it is recommended that SEM should be employed to test relationship between variables since it can explore complex relationships among variables such as direct, indirect, spurious, hierarchical and non-hierarchical.

Bad News

2021 ◽  
pp. 240-260
Author(s):  
Debasish Roy Chowdhury ◽  
John Keane
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Communication Networks ◽  
Bad News ◽  
Fake News ◽  
Media Environment ◽  
Media Frames ◽  
Mainstream Media ◽  
Bharatiya Janata Party ◽  
Media Communications

This chapter examines Indian media. Communications scholars have long argued that media sets the agenda for public opinion, first by drawing the attention of citizens to a particular issue, and then by defining it by means of comprehensible media ‘frames’ that act as cognitive shortcuts to understand issues. As in other so-called democracies, journalists working within India’s mainstream media are engaged 24/7 in framing narratives, making them indispensable for any government. Anti-Muslim messaging, generally subtle, has been the default media frame ever since the Hindu nationalist Bharatiya Janata Party (BJP) came to power in 2014. This coincided with the coming of communicative abundance, the profusion of new communication networks and technologies, and rapidly changing media consumption habits. Secretive organizations frame sophisticated misinformation campaigns to spread fake news and false claims through social media. In such a media environment marked by features common to despotisms like Vietnam, Iran, and Russia, where independent journalism is all but dead, self-censorship and toad-eating are rife.

scholarly journals Quantifying time-dependent Media Agenda and public opinion by topic modeling

2019 ◽  
Vol 524 ◽  
pp. 614-624 ◽  
Author(s):  
Sebastián Pinto ◽  
Federico Albanese ◽  
Claudio O. Dorso ◽  
Pablo Balenzuela
Keyword(s):  
Public Opinion ◽  
Topic Modeling ◽  
Time Dependent ◽  
Media Agenda

Timely Forecasts of Diffusion of Innovations: The Bass Model in Emerging Markets

2020 ◽  
pp. 097215092097349
Author(s):  
Suddhachit Mitra ◽  
Preeti Priya ◽  
Anand Venkatesh ◽  
Saswata N. Biswas
Keyword(s):  
Emerging Markets ◽  
Least Squares ◽  
Diffusion Of Innovations ◽  
Ordinary Least Squares ◽  
Optimization Techniques ◽  
Bass Model ◽  
Linear Least Squares ◽  
Diagnostic Measures ◽  
Gradient Based ◽  
Comprehensive Comparison

This article aims to establish a methodology to estimate the parameters of the Bass model of diffusion of innovations at the take-off stage of the innovation in emerging markets and thus draw timely diffusion forecasts. This article analyses four cases of diffusion of innovations in emerging markets. Besides gradient-based methods for model estimation such as ordinary least squares (OLS) and non-linear least squares (NLS), this article uses global optimization techniques such as genetic algorithms (GA) and simulated annealing (SA) with diffusion data till the take-off stage. This study attempts to respond to the problems of scant data by interpolation until the take-off stage. After that, a comprehensive comparison of different methods is made using the standard error diagnostic measures. The results indicate that a combination of NLS, GA and SA with interpolated data reduces error margins to a commonly acceptable level even with scant and noisy data, thus providing managers a methodology to make timely forecasts of diffusion of innovations in emerging markets.

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