scholarly journals Ethical Consumers’ Awareness of Vegan Materials: Focused on Fake Fur and Fake Leather

2021 ◽  
Vol 13 (1) ◽  
pp. 436
Author(s):  
Yeong-Hyeon Choi ◽  
Kyu-Hye Lee
Keyword(s):  
Animal Rights ◽  
Keyword Search ◽  
Animal Abuse ◽  
Ethical Awareness ◽  
Inverse Document Frequency ◽  
Animal Protection ◽  
Ethical Consumers ◽  
Search Volume ◽  
Document Frequency ◽  
The Relationship

With an increase in ethical awareness, people have begun to criticize the unethical issues associated with the use of animal materials. This study focused on the transition of global consumers’ awareness toward vegan materials and the relationship between the interest in ethical subjects such as animals, the environment, and vegan materials. For this purpose, consumers’ posts about fur/fake fur and leather/fake leather uploaded on Google and Twitter from 2008 to 2019 were utilized, and the Term Frequency-Inverse Document Frequency (Tf-idf) value was extracted using Python 3.7. Furthermore, the worldwide Google keyword search volume of each word was analyzed using Smart PLS 3.0 to investigate global consumers’ awareness. First, with time, consumers began relating animal materials such as fur and leather to topics such as animal rights, animal abuse, and animal protection. Second, as interest in “animal welfare” increased, interest in “fake fur” also rose, and as interest in “cruelty free” increased, interest in “fake fur”, “vegan fur”, and “vegan leather” also increased. Third, as consumers’ interest in the “environment” increased, interest in vegan materials such as “fake fur” and “fake leather” decreased. However, as interest in “eco” increased, interest in “vegan leather” also augmented.

Caring about Blood, Flesh, and Pain:Women's Standing in the Animal Protection Movement

2001 ◽  
Vol 9 (1) ◽  
pp. 43-61 ◽  
Author(s):  
Lyle Munro
Keyword(s):  
Animal Rights ◽  
Companion Animals ◽  
Drunk Driving ◽  
Women's Movements ◽  
Animal Abuse ◽  
Men And Women ◽  
Male And Female ◽  
Animal Protection ◽  
Mothers Against Drunk Driving ◽  
History Of

AbstractUsing the results of a survey of animal rights activists, advocates, and supporters, the paper reveals much more convergence (80%) than divergence (20%) of attitudes and actions by male and female animal protectionists. Analysis of the divergence suggests that the differences between men and women in the movement are contingent upon such things as early socialization, gendered work and leisure patterns, affinity with companion animals, ambivalence about science, and a history of opposition to nonhuman animal abuse by generations of female activists and animal advocates. Aside from the feminist and women's movements and groups like Mothers Against Drunk Driving, it is rare to find a social movement in which the standing of women eclipses those of their male colleagues. The paper suggests that animal protection remains a bastion of female activism and advocacy because women care about blood, flesh, and pain and, unlike earlier generations of animal activists, no longer are seen as a liability to the success of the movement.

scholarly journals Revealing Associations between Diagnosis Patterns and Acupoint Prescriptions Using Medical Data Extracted from Case Reports

2019 ◽  
Vol 8 (10) ◽  
pp. 1663 ◽  
Author(s):  
Cheol-Han Kim ◽  
Da-Eun Yoon ◽  
Ye-Seul Lee ◽  
Won-Mo Jung ◽  
Joo-Hee Kim ◽  
...  
Keyword(s):  
Network Analysis ◽  
Case Reports ◽  
Medical Data ◽  
Medical Doctors ◽  
Inverse Document Frequency ◽  
Qualitative And Quantitative ◽  
Bladder Disease ◽  
Document Frequency ◽  
The Relationship ◽  
Disease Specific

Objective: The optimal acupoints for a particular disease can be determined by analysis of diagnosis patterns. The objective of this study was to reveal the association between such patterns and the acupoints prescribed in clinical practice using medical data extracted from case reports. Methods: This study evaluated online virtual diagnoses made by currently practicing Korean medical doctors (N = 80). The doctors were presented with 10 case reports published in Korean medical journals and were asked to diagnose the patients and prescribe acupoints accordingly. A network analysis and the term frequency-inverse document frequency (tf-idf) method were used to analyse and quantify the relationship between diagnosis patterns and prescribed acupoints. Results: The network analysis showed that ST36, LI4, LR3, and SP6 were the most frequently used acupoints across all diagnoses. The tf-idf values showed the acupoints used for specific diseases, such as BL40 for bladder disease and LU9 for lung disease. Conclusions: The associations between diagnosis patterns and prescribed acupoints were identified using an online virtual diagnosis modality. Network and text mining analyses revealed commonly applied and disease-specific acupoints in both qualitative and quantitative terms.

scholarly journals Lyric Text Mining Of Dangdut: Visualizing The Selected Words And Word Pairs Of The Legendary Rhoma Irama’s Dangdut Song In The 1970s Era

2018 ◽  
Vol 4 (2) ◽  
pp. 9-17
Author(s):  
Tresna Maulana Fahrudin ◽  
Ali Ridho Barakbah
Keyword(s):  
Text Mining ◽  
Data Extraction ◽  
Way Of Life ◽  
Network Graph ◽  
Human Right ◽  
Inverse Document Frequency ◽  
Document Frequency ◽  
Song Lyrics ◽  
The Relationship ◽  
Word Frequencies

Dangdut is a new genre of music introduced by Rhoma Irama, Indonesian popular musician who was the Legendary dangdut singer in the 1970s era until now. The expression of  Rhoma Irama’s lyric has themes of the human being, the way of life, love, law and human right, tradition, social equality, and Islamic messages. But interestingly, the song lyrics were written by Rhoma Irama in the 1970s were mostly on the love song themes. In order to prove this, it is necessary to identify the songs through several approaches to explore the selected word and the relationship between word pairs. If each Rhoma Irama’s lyric is identified in text mining field, the lyric text extraction will be an interesting knowledge pattern. We collected the lyric from web were used as datasets, and then we have done the data extraction to store the component of lyric including the part and line of the song. We successfully applied the most word frequencies in the form of data visualization including bar chart, word cloud, term frequency-inverse document frequency, and network graph. As a results, several word pairs that often was used by Rhoma Irama in writing his song including heart-love (19 lines), heart-longing (13 lines), heart-beloved (12 lines), love-beloved (12 lines), love-longing (11 lines).

scholarly journals The Analysis of Proximity Between Subjects Based on Primary Contents Using Cosine Similarity on Lective

2017 ◽  
pp. 299-308
Author(s):  
Muhammad Andi Al-rizki ◽  
Galih Wasis Wicaksono ◽  
Yufis Azhar
Keyword(s):  
Cosine Similarity ◽  
High Similarity ◽  
Inverse Document Frequency ◽  
Term Frequency ◽  
Research Results ◽  
Document Frequency ◽  
Precision And Accuracy ◽  
The Relationship ◽  
Similarity Method

In education world, recognizing the relationship between one subject and another is imperative. By recognizing the relationship between courses, performing sustainability mapping between subjects can be easily performed.  Moreover, detecting and reducing any duplicated contents in several subjects will be also possible to execute. Of course, these conveniences will benefit lecturers, students and departments. It will ease the analysis and discussion processes between lecturers related to subjects in the same domain. In addition, students will conveniently choose a group of subjects they are interested in. Furthermore, departments can easily create a specialization group based on the similarity of the subjects and combine the courses possessing high similarity. In this research, given a good database, the relationship between subjects was calculated based on the proximity of the primary contents of the subjects. The feature used was term feature, in which value was determined by calculating TF-IDF (Term Frequency Inverse Document Frequency) from each term. In recognizing the value of proximity between subjects, cosine similarity method was implemented. Finally, testing was done utilizing precision, recall and accuracy method. The research results show that the precision and accuracy values are 90,91% and the recall value is 100%.

scholarly journals Media and promotional campaigns of the 'PETA' organization for the protection of animals

Napredak ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 103-118
Author(s):  
Tatjana Grubor
Keyword(s):  
Social Networks ◽  
Animal Rights ◽  
Individual Animal ◽  
Animal Protection ◽  
The Past ◽  
Media Space ◽  
The World ◽  
Large Audience ◽  
National Governments ◽  
The Relationship

This paper deals with the issue of the relationship between humans and animals in the past, from prehistory to the present day, and lays special emphasis on the ideas, goals, and achievements of the organization for the protection of animal rights PETA (People for the Ethical Treatment of Animals). As people themselves do not problematize their behavior towards animals, there are organizations that try to point out the greatest problems of inhumane treatment of animals in research laboratories, farms, the entertainment industry, but also as the result of the behavior of each individual. Animal protection societies operate in two ways, fighting large industries globally, forcing positive laws, lobbying national governments and international alliances and organizations, but also at the level of each person, trying to take small steps towards developing awareness of the need to care for animals and change society's attitudes towards them. The world's largest organization for the protection of animal rights, PETA, is leading in that effort with its activities and campaigns. Using all means, often on the verging on the scandalous, this organization grabs as much media space as possible, and with the development of modern social networks, it finally has daily access to a large audience of interested people around the world.

Retrospective analysis of complaints of animal abuse against animals in Pinhais, Paraná, Brazil

2017 ◽  
Vol XXII (127) ◽  
pp. 86-92
Author(s):  
Solange Aparecida Marconcin ◽  
Karyn Aparecida Rossa ◽  
Isabela Solá Chagas Lima Scalco ◽  
Luana Oliveira Leite ◽  
Rita de Cassia Maria Garcia
Keyword(s):  
Animal Welfare ◽  
Retrospective Analysis ◽  
Joint Action ◽  
Public Awareness ◽  
Family Members ◽  
Animal Abuse ◽  
Animal Protection ◽  
Awareness Programs ◽  
Inadequate Nutrition ◽  
The Relationship

The relationship between humans and their pets has become closer and more intense over the centuries. Currently, dogs and cats are considered family members in many households, participating actively in the routine of their tutors. However, despite the narrowing of laces, accounts of ill-treatment of animals are frequent. The aim of this study was to describe the characteristics of such complaints in Pinhais, PR, Brazil. 85.24% of the total number of 583 reports involved dogs. Most reports referred to abandonment (26.41%), lack of space (20.92%) and inadequate nutrition (15.09%). The results indicate that the population has become more sensitive to animal welfare, thus revealing the importance of joint action between animal protection agencies and public awareness programs.

scholarly journals Analysis of Matric Product Matching Between Cosine Similarity with Term Frequency-Inverse Document Frequency (TF-IDF) and Word2Vec in PT. Pricebook Digital Indonesia

2020 ◽  
pp. 105-112
Author(s):  
Harni Kusniyati ◽  
Arie Aditya Nugraha
Keyword(s):  
Word Embedding ◽  
Cosine Similarity ◽  
Consumer Experience ◽  
Inverse Document Frequency ◽  
Term Frequency ◽  
Document Frequency ◽  
The Relationship ◽  
Product Specifications ◽  
Similarity Method ◽  
Product Matching

Consumers today have the option to purchase products from thousands of e-commerce. However, the completeness of the product specifications and taxonomies used to organize products differently in different electronic shop differently. To improve the consumer experience, Pricebook approach for integration of the product through the website to find the cheapest price from various platforms. In our writing, we do approach by using a model of neural language such as TF-IDF (term frequency-inverse document frequency) as well as Word2vec by using the method of cosine similarity. TF-IDF is a way to give the relationship a word weighting (term) against the document. Semantic vector or word embedding is one way to represent the structure of a sentence will be in align with manipulating sentences into vector shapes with Word2Vec. Cosine similarity method is a method to calculate the similarity between two objects that is expressed in two vectors by using keywords (keywords) of a document as the size so that it leads to more products matching good performance and categorization. In addition, we compare the results of the representation of the TF-IDF with Word2vec against a number of the data.

Meat without Animals: Outcast Objects and the Improvement of London

2018 ◽  
Author(s):  
Ted Geier
Keyword(s):  
Animal Rights ◽  
Legal Reform ◽  
Meat Production ◽  
History Of ◽  
Relationship Of ◽  
The Relationship

Covers the long history of the Smithfield animal market and legal reform in London. Shows the relationship of civic improvement tropes, including animal rights, to animal erasure in the form of new foodstuffs from distant meat production sites. The reduction of lives to commodities also informed public abasement of the butchers.

scholarly journals Google search behavior for meningitis and its vaccines: an infodemiological study

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
John Angelo Luigi S. Perez ◽  
Adrian I. Espiritu ◽  
Roland Dominic G. Jamora
Keyword(s):  
Influenza Vaccine ◽  
Pneumococcal Vaccine ◽  
Rank Correlation ◽  
Infectious Agents ◽  
Online Behavior ◽  
Online Search ◽  
Search Volume ◽  
Search Patterns ◽  
Google Search ◽  
The Relationship

Abstract Background The internet has made significant contributions towards health education. Analyzing the pattern of online behavior regarding meningitis and vaccinations may be worthwhile. It is hypothesized that the online search patterns in meningitis are correlated with its number of cases and the search patterns of its related vaccines. Methods This was an infodemiological study that determined the relationship among online search interest in meningitis, its worldwide number of cases and its associated vaccines. Using Google Trends™ Search Volume Indices (SVIs), we evaluated the search queries “meningitis,” “pneumococcal vaccine,” “BCG vaccine,” “meningococcal vaccine” and “influenza vaccine” in January 2021, covering January 2008 to December 2020. Spearman rank correlation was used to determine correlations between these queries. Results The worldwide search interest in meningitis from 2008 to 2020 showed an average SVI of 46 ± 8.8. The most searched topics were symptoms, vaccines, and infectious agents with SVIs of 100, 52, and 39, respectively. The top three countries with the highest search interest were Ghana, Kazakhstan, and Kenya. There were weak, but statistically significant correlations between meningitis and the BCG (ρ = 0.369, p < 0.001) and meningococcal (ρ = 0.183, p < 0.05) vaccines. There were no statistically significant associations between the number of cases, influenza vaccine, and pneumococcal vaccine. Conclusion The relationships among the Google SVIs for meningitis and its related vaccines and number of cases data were inconsistent and remained unclear. Future infodemiological studies may expand their scopes to social media, semantics, and big data for more robust conclusions.

scholarly journals Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Peter Brown ◽  
Aik-Choon Tan ◽  
Mohamed A El-Esawi ◽  
Thomas Liehr ◽  
Oliver Blanck ◽  
...  
Keyword(s):  
Literature Search ◽  
Relevant Literature ◽  
Biomedical Literature ◽  
Medical Subject Headings ◽  
Document Similarity ◽  
Inverse Document Frequency ◽  
Research Fields ◽  
Experience Levels ◽  
Document Frequency ◽  
Systematic Biases

Abstract Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.

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