scholarly journals Quantifying emotionally grounded discursive knowledge with cognitive-affective maps

2021 ◽  
Author(s):  
Jasmin Luthardt ◽  
Jonathan Howard Morgan ◽  
Inka Bormann ◽  
Tobias Schröder
Keyword(s):  
Quantitative Methods ◽  
Belief Systems ◽  
Visual Representations ◽  
Three Dimensions ◽  
Third Party ◽  
Group Level ◽  
Text Data ◽  
Data Set ◽  
Network Similarity

AbstractBelief systems matter for all kinds of human social interaction. People have individual cognitions and feelings concerning processes in their environment, which is why they may evaluate them differently. Belief systems can be visualized with cognitive-affective maps (CAMs; as reported by Thagard (in: McGregor (ed) EMPATHICA: A computer support system with visual representations for cognitive-affective mapping, AAAI Press, CA, 2010)). However, it is unclear whether CAMs can be constructed in an intersubjective way by different researchers attempting to map the beliefs of a third party based on qualitative text data. To scrutinize this question, we combined qualitative strategies and quantitative methods of text and network analysis in a case study examining belief networks about participation. Our data set consists of 10 sets of two empirical CAMs: the first CAM was created based on participants’ freely associating concepts related to participation in education (N = 10), the second one was created based on given text data which the participants represented as a CAM following a standardized instruction manual (N = 10). Both CAM-types were compared along three dimensions of similarity (network similarity, concept association similarity, affective similarity). On all dimensions of similarity, there was substantially higher intersubjective agreement in the text-based CAMs than in the free CAMs, supporting the viability of cognitive affective mapping as an intersubjective research method for studying the emotional coherence of belief systems and discursive knowledge. In addition, this study highlights the potential for identifying group-level differences based on how participants associate concepts.

scholarly journals Statistical infarction: A postmortem of the Cornell Food and Brand Lab pizza publications

2017 ◽  
Author(s):  
Jordan Anaya ◽  
Tim van der Zee ◽  
Nick Brown
Keyword(s):  
Eating Habits ◽  
Initial Response ◽  
Third Party ◽  
New Technique ◽  
Data Set ◽  
Growing Media ◽  
Media Attention ◽  
First Time ◽  
Suitable Case

We previously reported over 150 inconsistencies in a series of four articles (the "pizza papers") from the Cornell Food and Brand Lab that described a study of eating habits at an all-you-can-eat pizza buffet. The lab's initial response led us to investigate more of their work, and our investigation has now identified issues with at least 45 publications from this lab. Perhaps because of the growing media attention, Cornell and the lab have released a statement concerning the pizza papers, which included a response to the inconsistencies, along with data and code. Many of the inconsistencies were identified with the new technique of granularity testing, and this case has the highest density of granularity inconsistencies that we know of. This is also the first time a data set has been made public after granularity concerns were raised, making it a highly suitable case study for showing the accuracy and potential of this technique. It is also important that a third party audit the lab's response, given the continuing investigation of misconduct and presumably future reports and data releases. Our careful inspection of the data set suggests no evidence of fabrication, but we found the lab's report confusing, incomplete, and error prone. In addition, we found the number of missing, unusual, and logically impossible responses in the data set highly concerning. Unfortunately, given the unsound theory, poor methodology, questionable data, and countless errors, we find it remarkable that these four papers were published and recommend retraction of all four papers.

scholarly journals Evaluating Energy Sustainability Using the Pressure-State-Response and Improved Matter-Element Extension Models: Case Study of China

2019 ◽  
Vol 11 (1) ◽  
pp. 290 ◽  
Author(s):  
Shuyu Li ◽  
Rongrong Li
Keyword(s):  
Quantitative Methods ◽  
Evaluation Index System ◽  
Three Dimensions ◽  
Energy Sustainability ◽  
Weighting Method ◽  
Energy And Environment ◽  
State Response ◽  
Energy Evaluation ◽  
Pressure State

Most existing studies on energy sustainability have focused on qualitative research. Few studies have applied quantitative methods, and there has not been a systematic review of energy sustainability. To fill this gap, this study first developed a sustainable energy evaluation index system consisting of 20 indicators across the three dimensions of economy, energy, and environment based on the pressure-state-response (PSR) model. The weights of these indicators were then determined in conjunction with the weighting method. Finally, the matter-element extension method was improved to quantify energy sustainability. The proposed method was applied to evaluate China’s energy sustainability status from 2000 to 2015. The results show that China’s status continued to improve; however, it remained at a low level. To improve China’s energy sustainability, more efforts are needed in the economic, energy, and environmental dimensions.

Pattern Recognition of Subconscious Underpinnings of Cognition using Ultrametric Topological Mapping of Thinking and Memory

2014 ◽  
Vol 8 (4) ◽  
pp. 1-16 ◽  
Author(s):  
Fionn Murtagh
Keyword(s):  
Case Studies ◽  
Theory And Practice ◽  
Large Set ◽  
Thought Processes ◽  
Unconscious Thought ◽  
Text Data ◽  
Data Set ◽  
Ultrametric Topology ◽  
Textual Data

The author reviews the theory and practice of determining what parts of a data set are ultrametric. He describes the potential relevance of ultrametric topology as a framework for unconscious thought processes. This view of ultrametric topology as a framework that complements metric-based, conscious, Aristotelian logical reasoning comes from the work of the Chilean psychoanalyst, Ignacio Matte Blanco. Taking text data, the author develops an algorithm for finding local ultrametricity in such data. He applies that in two case studies. The first relates to a large set of dream reports, and therefore can possibly recall traces of unconscious thought processes. The second case study uses Twitter social media, and has the aim of picking up underlying associations. The author's case studies are selective in regard to names of people and objects, and are focused in order to highlight the principle of his approach, which is one of particular pattern finding in textual data.

The Toumba building at Lefkandi: a statistical method for detecting a design-unit

2004 ◽  
Vol 99 ◽  
pp. 257-271
Author(s):  
Jari Pakkanen
Keyword(s):  
Monte Carlo ◽  
Computer Simulations ◽  
Iron Age ◽  
Quantitative Methods ◽  
Statistical Problem ◽  
Early Iron Age ◽  
Second Phase ◽  
Data Set ◽  
Methodological Paper

This methodological paper uses the measurements of the Early Iron Age Toumba building at Lefkandi to study whether a single design-unit can be detected in the data set. Cosine quantogram analysis is used in the initial analysis of the building dimensions and, in the second phase, the relevance of the obtained results is calculated by using Monte Carlo computer simulations. A statistically significant unit of c. 49 cm can be isolated, but because of the very limited number of precise dimensions, this result should only be accepted with caution. The case study demonstrates how the complex statistical problem of deriving the lengths of possibly used design-units in ancient architecture can be approached; metrological analyses can only gain from employing appropriate quantitative methods.

scholarly journals Statistical infarction: A postmortem of the Cornell Food and Brand Lab pizza publications

2017 ◽  
Author(s):  
Jordan Anaya ◽  
Tim van der Zee ◽  
Nick Brown
Keyword(s):  
Eating Habits ◽  
Initial Response ◽  
Third Party ◽  
New Technique ◽  
Data Set ◽  
Growing Media ◽  
Media Attention ◽  
First Time ◽  
Suitable Case

We previously reported over 150 inconsistencies in a series of four articles (the "pizza papers") from the Cornell Food and Brand Lab that described a study of eating habits at an all-you-can-eat pizza buffet. The lab's initial response led us to investigate more of their work, and our investigation has now identified issues with at least 45 publications from this lab. Perhaps because of the growing media attention, Cornell and the lab have released a statement concerning the pizza papers, which included a response to the inconsistencies, along with data and code. Many of the inconsistencies were identified with the new technique of granularity testing, and this case has the highest density of granularity inconsistencies that we know of. This is also the first time a data set has been made public after granularity concerns were raised, making it a highly suitable case study for showing the accuracy and potential of this technique. It is also important that a third party audit the lab's response, given the continuing investigation of misconduct and presumably future reports and data releases. Our careful inspection of the data set suggests no evidence of fabrication, but we found the lab's report confusing, incomplete, and error prone. In addition, we found the number of missing, unusual, and logically impossible responses in the data set highly concerning. Unfortunately, given the unsound theory, poor methodology, questionable data, and countless errors, we find it remarkable that these four papers were published and recommend retraction of all four papers.

Diagnostics of professional competence of IT students based on digital footprint data

2020 ◽  
pp. 4-11
Author(s):  
I. G. Zakharova ◽  
Yu. V. Boganyuk ◽  
M. S. Vorobyova ◽  
E. A. Pavlova
Keyword(s):  
Information Technology ◽  
Educational Program ◽  
Professional Competence ◽  
Objective Data ◽  
Text Data ◽  
Data Set ◽  
Job Requirements ◽  
Digital Footprint ◽  
Graduate Employment ◽  
The University

The article goal is to demonstrate the possibilities of the approach to diagnosing the level of IT graduates’ professional competence, based on the analysis of the student’s digital footprint and the content of the corresponding educational program. We describe methods for extracting student professional level indicators from digital footprint text data — courses’ descriptions and graduation qualification works. We show methods of comparing these indicators with the formalized requirements of employers, reflected in the texts of vacancies in the field of information technology. The proposed approach was applied at the Institute of Mathematics and Computer Science of the University of Tyumen. We performed diagnostics using a data set that included texts of courses’ descriptions for IT areas of undergraduate studies, 542 graduation qualification works in these areas, 879 descriptions of job requirements and information on graduate employment. The presented approach allows us to evaluate the relevance of the educational program as a whole and the level of professional competence of each student based on objective data. The results were used to update the content of some major courses and to include new elective courses in the curriculum.

An Author as Literature. (Visual) Autofiction of Dorota Masłowska

2016 ◽  
Author(s):  
Anna Michalak
Keyword(s):  
New Media ◽  
Cultural Practices ◽  
Conceptual Art ◽  
Visual Representations ◽  
The Creation

Using the promotional meeting of Dorota Masłowska’s book "More than you can eat" (16 April 2015 in the Bar Studio, Warsaw), as a case study, the article examines the role author plays in it and try to show how the author itself can become the literature. As a result of the transformation of cultural practices associated with the new media, the author’s figure has gained much greater visibility which consequently changed its meaning. In the article, Masłowska’s artistic strategy is compared to visual autofiction in conceptual art and interpreted through the role of the performance and visual representations in the creation of the image or author’s brand.

A Review on Sentiment Classification: Natural Language Understanding

2019 ◽  
Vol 13 (1) ◽  
pp. 20-27 ◽  
Author(s):  
Srishty Jindal ◽  
Kamlesh Sharma
Keyword(s):  
Natural Language ◽  
Sentiment Analysis ◽  
Social Networking Sites ◽  
Natural Language Understanding ◽  
Business Analytics ◽  
Language Understanding ◽  
Text Data ◽  
Data Set ◽  
Market Positioning ◽  
Illegal Activities

Background: With the tremendous increase in the use of social networking sites for sharing the emotions, views, preferences etc. a huge volume of data and text is available on the internet, there comes the need for understanding the text and analysing the data to determine the exact intent behind the same for a greater good. This process of understanding the text and data involves loads of analytical methods, several phases and multiple techniques. Efficient use of these techniques is important for an effective and relevant understanding of the text/data. This analysis can in turn be very helpful in ecommerce for targeting audience, social media monitoring for anticipating the foul elements from society and take proactive actions to avoid unethical and illegal activities, business analytics, market positioning etc. Method: The goal is to understand the basic steps involved in analysing the text data which can be helpful in determining sentiments behind them. This review provides detailed description of steps involved in sentiment analysis with the recent research done. Patents related to sentiment analysis and classification are reviewed to throw some light in the work done related to the field. Results: Sentiment analysis determines the polarity behind the text data/review. This analysis helps in increasing the business revenue, e-health, or determining the behaviour of a person. Conclusion: This study helps in understanding the basic steps involved in natural language understanding. At each step there are multiple techniques that can be applied on data. Different classifiers provide variable accuracy depending upon the data set and classification technique used.

Parent and Grandparent Relationships in Emerging Adulthood

2018 ◽  
Author(s):  
Michael W. Pratt ◽  
M. Kyle Matsuba
Keyword(s):  
Emerging Adulthood ◽  
Attachment Theory ◽  
Emerging Adults ◽  
Family Relationships ◽  
Longitudinal Research ◽  
Study Data ◽  
Family Development ◽  
Data Set ◽  
Theory Framework

Chapter 7 begins with an overview of Erikson’s ideas about intimacy and its place in the life cycle, followed by a summary of Bowlby and Ainsworth’s attachment theory framework and its relation to family development. The authors review existing longitudinal research on the development of family relationships in adolescence and emerging adulthood, focusing on evidence with regard to links to McAdams and Pals’ personality model. They discuss the evidence, both questionnaire and narrative, from the Futures Study data set on family relationships, including emerging adults’ relations with parents and, separately, with grandparents, as well as their anticipations of their own parenthood. As a way of illustrating the key personality concepts from this family chapter, the authors end with a case study of Jane Fonda in youth and her father, Henry Fonda, to illustrate these issues through the lives of a 20th-century Hollywood dynasty of actors.

Vocational Development in Emerging Adulthood

2018 ◽  
Author(s):  
Michael W. Pratt ◽  
M. Kyle Matsuba
Keyword(s):  
Turning Point ◽  
Life Stories ◽  
Life Story ◽  
Emerging Adult ◽  
Vocational Development ◽  
Data Set ◽  
The World ◽  
Key Concepts

Chapter 6 reviews research on the topic of vocational/occupational development in relation to the McAdams and Pals tripartite personality framework of traits, goals, and life stories. Distinctions between types of motivations for the work role (as a job, career, or calling) are particularly highlighted. The authors then turn to research from the Futures Study on work motivations and their links to personality traits, identity, generativity, and the life story, drawing on analyses and quotes from the data set. To illustrate the key concepts from this vocation chapter, the authors end with a case study on Charles Darwin’s pivotal turning point, his round-the-world voyage as naturalist for the HMS Beagle. Darwin was an emerging adult in his 20s at the time, and we highlight the role of this journey as a turning point in his adult vocational development.

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