scholarly journals Scuba Diving Experience and Sustainability: An Assessment of Online Travel Reviews

2018 ◽  
Vol 9 ◽  
pp. 43-52 ◽  
Author(s):  
Peunjodi Naidoo ◽  
Prabha Ramseook-Munhurrun ◽  
Jing Li
Keyword(s):  
Text Analysis ◽  
Physical Environment ◽  
Scuba Diving ◽  
Tourism Industry ◽  
Small Island ◽  
Analysis Software ◽  
Unsupervised Analysis ◽  
Online Travel Reviews ◽  
Tourism And Hospitality ◽  
Online Travel

Scuba diving is a popular activity in small island destinations which is on the rise. However, it is particularly important to preserve the physical environment for small island developing states due to their unique biodiversity and fragile ecosystems. Scuba diving tourism in island destinations is provided mainly by dive operators who are responsible to deliver the scuba diving experience to tourists. However, despite the importance of sustainability for the tourism industry, it is unclear to which extent the marine environment or green issues are important for consumers. Studies are increasingly suggesting that sustainability is an important feature considered by consumers. However, information is sparse regarding the extent to which sustainability is a key component for customers when evaluating the scuba diving experience. In this study, 3109 text reviews from the Trip Advisor website across all 57 listed diving operators in Mauritius were selected for data analysis. Th e present study uses Leximancer, a text analysis software that conducts unsupervised analysis of natural language texts provided in an electronic format.The Gaze: Journal of Tourism and Hospitality Vol.9 2018 p.43-52

scholarly journals A posthumanist pedagogy using digital text analysis to enhance critical thinking in higher education

2019 ◽  
Vol 35 (4) ◽  
pp. 845-880
Author(s):  
Kieran O'Halloran
Keyword(s):  
Higher Education ◽  
Critical Thinking ◽  
Text Analysis ◽  
Status Quo ◽  
Analysis Software ◽  
Education Students ◽  
Digital Text ◽  
The Status ◽  
Project Assignment ◽  
Independent Thinking

Abstract I model a critical posthumanist pedagogy that uses text analysis software and is aimed at higher education students. A key purpose of the pedagogy is to help students enhance empathetic, critical and independent thinking. For their project assignment, the student chooses an unfamiliar campaign seeking to eliminate suffering and extend rights. They gather all texts from the campaign website into a corpus, which thus represents the campaign writ large. Then they use appropriate software to ascertain, efficiently and rigorously, common campaign concerns across this corpus. This puts students in a position to discern any significant concerns in the campaign corpus that are not addressed in text(s) supporting the status quo which the campaign opposes. Should significant omissions be found, students critically evaluate the status quo text(s) from the campaign’s perspective. Since this perspective derives from the student identifying (at least temporarily) with software generated data, it is a posthuman subjectivity. Engaging digitally and empathetically with a campaign’s data at scale for creation of a posthuman subjectivity can broaden awareness of disadvantage, discrimination, and suffering as well as expand horizons. Moreover, at the end of the assignment, the student is expected to formulate their own position vis-à-vis the previously unfamiliar campaign. Conditions have been created then for the student to enhance independent thinking too.

scholarly journals Development of the text analysis software agent (chat bot) for the library based on the question and answer system TWIN

2019 ◽  
Vol 30 ◽  
pp. 04006
Author(s):  
Anastasia Ivanovskaya ◽  
Konstantin Aksyonov ◽  
Igor Kalinin ◽  
Yuriy Chiryshev ◽  
Olga Aksyonova
Keyword(s):  
Text Analysis ◽  
Software Agent ◽  
Analysis Software ◽  
Response System ◽  
System A ◽  
Correct Information ◽  
Question And Answer ◽  
Chat Bot

The development of a text analysis software agent is presented for a library based on the TWIN question-response system. A review of modern platforms for creating chat bots. The results of experiments with a trained text analysis software agent are described. The trained agent fully provided correct information during the experiments.

Ensemble Methods for Improving Classification of Data Produced by Latent Dirichlet Allocation

2019 ◽  
Vol 0 (8/2018) ◽  
pp. 17-28
Author(s):  
Maciej Jankowski
Keyword(s):  
Text Analysis ◽  
Large Scale ◽  
Latent Dirichlet Allocation ◽  
Previous Analysis ◽  
Ensemble Methods ◽  
Topic Modelling ◽  
New Methods ◽  
Data Scientist ◽  
Dirichlet Allocation

Topic models are very popular methods of text analysis. The most popular algorithm for topic modelling is LDA (Latent Dirichlet Allocation). Recently, many new methods were proposed, that enable the usage of this model in large scale processing. One of the problem is, that a data scientist has to choose the number of topics manually. This step, requires some previous analysis. A few methods were proposed to automatize this step, but none of them works very well if LDA is used as a preprocessing for further classification. In this paper, we propose an ensemble approach which allows us to use more than one model at prediction phase, at the same time, reducing the need of finding a single best number of topics. We have also analyzed a few methods of estimating topic number.

scholarly journals Representação social da aposentadoria para professores universitários

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Luana De Barros Campos Amaral ◽  
Tatiana Lucena Torres
Keyword(s):  
Social Security ◽  
Text Analysis ◽  
Social Representations ◽  
Social Representation ◽  
Northeastern Brazil ◽  
Analysis Software ◽  
University Professors ◽  
The Social ◽  
Life Itself ◽  
New Phase

RESUMO: O objetivo do presente estudo foi analisar as representações sociais da aposentadoria para professores que trabalham em duas universidades federais do nordeste brasileiro. Foram realizadas vinte entrevistas narrativas, pareadas por sexo e instituição, com professores universitários que possuíam 50 anos ou mais de idade. As entrevistas transcritas foram analisadas com auxílio de software de análise textual, do tipo lexicográfica. Os resultados indicaram a composição de seis classes textuais e as representações sociais mais fortes se referiam à aposentadoria como nova etapa de vida, retorno à família, envelhecimento, viagens e lazer. Para os entrevistados, as representações sociais da aposentadoria foram positivas, no entanto, a perspectiva de um trabalho satisfatório, somado ao medo em relação às mudanças previdenciárias e a própria vida, reforçam a intenção de adiar a aposentadoria. Não houve diferenças significativas entre instituições, o que demonstra certa homogeneidade das representações para esse grupo profissional.Palavras-chaves: aposentadoria; professores; representação social; universidade federal.ABSTRACT: This study aimed to analyze social representations of retirement among professors that work at two federal universities in northeastern Brazil. Twenty narrative interviews were carried out, paired by gender and institution, with university professors aged 50 and above. The transcribed interviews were analyzed with the aid of lexicographical text analysis software. The results indicated six text categories and the strongest social representations referred to retirement as a new phase in life, a return to family, aging, travel and leisure. For the interviewees, the social representations of retirement were positive, however, the prospect of a satisfactory job, added to the fear in relation to social security changes and life itself, reinforce the intention to postpone retirement. There were no significant differences between institutions, which demonstrates a certain homogeneity in representations among this professional group.Keywords: retirement; professors; social representation; federal university.

scholarly journals O sentimento político em redes sociais: big data, algoritmos e as emoções nos tweets sobre o impeachment de Dilma Rousseff | Political sentiment in social networks: big data, algorithims and emotions in tweets about the impeachment of Dilma Rousseff

2017 ◽  
Vol 13 (2) ◽  
Author(s):  
Fabio Malini ◽  
Patrick Ciarelli ◽  
Jean Medeiros
Keyword(s):  
Social Networks ◽  
Genetic Algorithms ◽  
Big Data ◽  
Sentiment Analysis ◽  
Text Analysis ◽  
Negative Polarization ◽  
Political Networks ◽  
Networks Analysis ◽  
Fear And Anxiety

Resumo Este artigo se propõe a ampliar a metodologia perspectivista (MALINI, 2016) de análise de redes sociais, incorporando um procedimento de análise dos sentimentos das mensagens postadas em redes de controvérsias políticas, em particular, em dois momentos distintos da campanha pelo impeachment da presidenta Dilma. O primeiro é o período da eclosão das manifestações antipetistas, no dia 15 de março de 2015. O segundo, dia 27 de agosto de 2016, quando a presidenta é deposta do cargo. Realiza uma revisão sobre a análise de sentimentos em megadados do Twitter e constrói uma metodologia que combina classificação humana de textos com aplicação de algoritmos genéticos de análise de textos, no intuito de analisar sentimentos genéricos (baseado na polarização positivo/negativos) e sentimento específicos, baseados nas seguintes emoções: Alegria, Raiva, Medo, Antecipação, Desgosto, Tristeza, Surpresa e Confiança. Conclui demonstrando que os movimentos pró e anti-Dilma são marcados pelo predomínio de sentimento de raiva, medo e ansiedade, confirmando a hipótese que a trolagem ofensiva demarca o estilo da indignação propagada em redes políticas no Twitter brasileiro.  Palavras-Chave: Análise de Sentimento; Big Data; Redes; Política; Twitter.Abstract This article aims to expand the perspectivist methodology (Malini, 2016) of social networks analysis, incorporating a proceeding of sentiment analysis of the messages posted in networks of political controversies, in particular, in two distinct moments of the campaign for the impeachment of President Dilma. The first is the period of the outbreak of PT protests, on March 15, 2015. The second, on August 27, 2016, when the president is deposed. We will be doing a theoretical review about sentiment analysis in Big Data on Twitter to build a methodology that combines human classification of texts with the application of genetic algorithms of text analysis and to analyze generic sentiments (based on positive / negative polarization) and specific sentiment, based on emotions like Joy, Anger, Fear, Anticipation, Disgust, Sadness, Surprise and Trust. It concludes by demonstrating that pro and anti-Dilma movements are marked by a predominance of anger, fear and anxiety, confirming the hypothesis that an offensive trolling demarcates the style of indignation propagated by political networks in Brazilian Twitter.Keywords: Sentiment Analysis; Big Data; Social Network; Politics; Twitter. 

scholarly journals Ternary Classification of Product Based Reviews: Survey, Open Issues and New Approach for Sentiment Analysis

2021 ◽  
Vol 1 (2) ◽  
pp. 1-8
Author(s):  
Sushila Sonare ◽  
Megha Kamble
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Text Analysis ◽  
Text Data ◽  
New Approach ◽  
Meaningful Information ◽  
Multi Class Classification ◽  
Almost All ◽  
Open Issues

Now-a-days, it is very common that the customers share their thoughts about any product, brand and their experience in social media. The analysts collect these reviews and process it, to extract meaningful information about the product. The beauty of social media is, it’s involved in all the domains. So the analysts got reviews from different social media and platforms for almost all kind of thing. The Sentiment Analysis is applied to predict outcomes for getting useful information, for ex.; like predict the blockbuster for a movie, rating for any new launches and many more. This type of prediction is really helpful for the customer to buy any goods or take any services in this competitive world. This paper is focused on e-commerce website reviews which are normally in text form with some special characters and some symbols (emojis). Each word in this text set got some meaning in terms of context, emotion and prior experience. These characteristics contribute to some of the features of text data for prediction. The objective of this paper is to compile existing research works on text analysis and emotion based analysis. The open issues and challenges of document based sentiment analysis are also discussed. The paper concluded with proposing a new approach of multi class classification. Ternary classification for classes positive, negative and neutral is suggested primarily for product based text and emoji reviews on Twitter social media.

scholarly journals EDUCATION OF ISLAMIC AESTHETICS FOUND IN AL-QUR’AN SURAH AR-RAHMAN

2020 ◽  
Vol 14 (1) ◽  
pp. 59-71
Author(s):  
Ali Fauzi
Keyword(s):  
Qualitative Research ◽  
Content Analysis ◽  
Text Analysis ◽  
Figurative Language ◽  
Deep Understanding ◽  
Phenomenological Approach ◽  
Figure Of Speech

In Al-Qur’an Surah Ar-Rahman, The researcher finds Education of Islamic Aesthetics accumulated in figurative language.  However, the Moslems just recite and do not try to know and to analyze it. The researcher chooses the title “Education of Islamic Aesthetics Found in Al-Qur’an Surah Ar-Rahman” and formulates the problem: How is the education of Islamic aesthetics found in Al-Qur’an Surah Ar-Rahman? The objective of the research is to describe the education of Islamic aesthetics he finds in Al-Qur’an Surah Ar-Rahman. The researcher hopes that this research will be useful for all sides. In order that he has knowledge about Education of Islamic Aesthethic in general and aesthetics in form of figurative language in special, he has to read many references as the basic of theories before. In the research, he uses phenomenological approach and in interpreting phenomena and facts, he uses hermeneutics. The research is qualitative research in form of content analysis and the method of research is descriptive-text analysis. The data in this research is in form of words, phrases, sentences, and verses taken from the Holy Al-Qur’an surah Ar-Rahman. The researcher collects the data by observing the text of Al-Qur’an Surah Ar-Rahman, and documenting them based on the classification of education of Islamic aesthetics accumulated in figurative language. He then analyzes the data by reducting, presenting and concluding them so that the data he uses are really valid. The researcher then describes the data of Education of Islamic aesthetics accumulated in form of figurative language he finds in the Al-Qur’an surah Ar-Rahmanelaborated in many kinds of figure of speech such as alliteration, antithesis, euphemism, personification, hyperbole, pleonasm, irony, antonomasia and apophasis. The researcher describes the data and analyzes them one by one using hermeneutics in the discussion. The researcher then concludes that in Al-Qur’an surah Ar-Rahman, he finds education of aesthetics the moslems must know. He also suggests the Moslems to recite and analyze it in order to get deep understanding on the verses and Surah Ar-Rahman.

scholarly journals Decision Support System Using Cloud-Based Moka Pos Application To Easy In Input In Orange Carwash Blulukan Flash N0.110 Colomadu

2020 ◽  
Vol 1 (3) ◽  
pp. 66-69
Author(s):  
Ayu Sri Muryani ◽  
Muqorobin Muqorobin
Keyword(s):  
Requirements Analysis ◽  
Software Requirements ◽  
Analysis Software ◽  
Service Business ◽  
Service Information ◽  
Heritage Studies ◽  
Car Wash ◽  
Software Requirements Analysis ◽  
Computerized System

Orange Carwash is a car wash service business that has been running in 2018, Orange Car. The wash address that I studied is located at Jalan Adi Sucipto no.110 Blulukan Colomadu In running a car wash service business, Orange Carwash tries to provide services to customers, regarding inputting types of washing products, member entry, express washing promos, and payment transaction methods. The system used is still classified as manual. For the purpose of this research, it really helps companies in terms of promoting and introducing products to car wash consumers with a computerized system using the cloud-based Moka Pos application. The method in this research is through observation, interviews, documentation, and heritage studies (looking for references from books or journals). The system design is made with context diagrams, HIPO, DAD, input output design, hardware requirements analysis, software requirements analysis. By using online input, the cashier will find it easier to group the washing type product data, as well as compile accurate and efficient reports. The final result of designing an online car wash service information system, using the Moka Pos application, in the form of sales report recap data and the number of types of washing products, classification of types of washing products, and the washer name of each cashier, which will be designed by the car wash. Oranger Carwash.

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