scholarly journals An Enhanced Approach for Using Data Visualization for Sentiment Analysis and Auto Summarization Data

2018 ◽  
Vol 12 (9) ◽  
pp. 190
Author(s):  
Osama Mohammad Rababah ◽  
Esra F. Alzaghoul ◽  
Hussam N. Fakhouri
Keyword(s):  
Sentiment Analysis ◽  
Data Visualization ◽  
Full Text ◽  
Visual Representation ◽  
The Other ◽  
The Internet ◽  
Original Text ◽  
Text Data ◽  
Data Summarization ◽  
Using Data

With the rapid increase in the size of the data over the internet there is a need for new studies for text data summarization and representation; rather than storing the full text or reading the full text we can store and read a summary that represent the original text. Furthermore, there is a need also to represent the summarized text with visual representation; one picture worth ten thousandwords. In this paper we propose an approach for visual representation of the summarized text;visual resources give creative control over how message is perceived andprovide a faster way to know what where the text about.This approach were implemented and tested on a sample of two datasets one of 50 texts and the other dataset of 80 positive and negative movie comments, the evaluation has been done visually and the percent of success cases has been reported, the precision and recall has been calculated.

scholarly journals Text Analysis with JSTOR Archives

2018 ◽  
Vol 4 ◽  
pp. 237802311880926
Author(s):  
John A. Bernau
Keyword(s):  
Social Sciences ◽  
Text Analysis ◽  
Visual Representation ◽  
Text Data ◽  
The Social ◽  
Using Data ◽  
Sociology Journals

I provide a visual representation of keyword trends and authorship for two flagship sociology journals using data from JSTOR’s Data for Research repository. While text data have accompanied the digital spread of information, it remains inaccessible to researchers unfamiliar with the required preprocessing. The visualization and accompanying code encourage widespread use of this source of data in the social sciences.

scholarly journals Internet Financial and Environmental Disclosures by Malaysian Companies

2009 ◽  
Vol 3 (1) ◽  
pp. 3 ◽  
Author(s):  
Ali Saleh Alarussi ◽  
Mustafa Mohd Hanefah ◽  
Mohamad Hisyam Selamat
Keyword(s):  
Firm Size ◽  
Chief Executive ◽  
The Other ◽  
Financial Disclosure ◽  
The Internet ◽  
Environmental Disclosure ◽  
Environmental Disclosures ◽  
Using Data ◽  
The Relationship ◽  
Significant Factors

This paper investigates whether determinants of financial disclosure are similar to environmental disclosure through the Internet. In other words, this paper examines the relationship between Internet financial disclosure (IFD), Internet environmental disclosures (IED) and six variables, namely, ethnic of chief executive officer (CEO), leverage, level of technology, listing status, profitability, and firm size. Six hypotheses formulated in this study were analyzed using data collected from the websites of 189 Malaysian listed companies in 2006. The results indicate that level of technology, ethnic of CEO and firm size are significant factors in explaining both IFD and IED. It is also observed that listing status is positively related to the level of IFD but not IED. On the other hand, profitability is significant factor in explaining the level of IED but not IFD. Finally, leverage is not significantly related to both IFD and IED. <br /><br />

Using sentiment analysis to review patient satisfaction data located on the internet

2015 ◽  
Vol 29 (2) ◽  
pp. 221-233 ◽  
Author(s):  
Anthony M. Hopper ◽  
Maria Uriyo
Keyword(s):  
Sentiment Analysis ◽  
The Internet ◽  
Data Set ◽  
Web Based ◽  
Content Type ◽  
Meaningful Information ◽  
Patient Feedback ◽  
Select Group ◽  
Healthcare Administrators ◽  
Using Data

Purpose – The purpose of this paper is to test the usefulness of sentiment analysis and time-to-next-complaint methods in quantifying text-based information located on the internet. As important, the authors demonstrate how managers can use time-to-next-complaint techniques to organize sentiment analysis derived data into useful information, which can be shared with doctors and other staff. Design/methodology/approach – The authors used sentiment analysis to review patient feedback for a select group of gynecologists in Virginia. The authors utilized time-to-next-complaint methods along with other techniques to organize this data into meaningful information. Findings – The authors demonstrated that sentiment analysis and time-to-next-complaint techniques might be useful tools for healthcare managers who are interested in transforming web-based text into meaningful, quantifiable information. Research limitations/implications – This study has several limitations. For one thing, neither the data set nor the techniques the authors used to analyze it will account for biases that resulted from selection issues related to gender, income, and culture, as well as from other socio-demographic concerns. Additionally, the authors lacked key data concerning patient volumes for the targeted physicians. Finally, it may be difficult to convince doctors to consider web-based comments as truthful, thereby preventing healthcare managers from using data located on the internet. Practical implications – The report illustrates some of the ways in which healthcare administrators can utilize sentiment analysis, along with time-to-next-complaint techniques, to mine web-based, patient comments for meaningful information. Originality/value – The paper is one of the first to illustrate ways in which administrators at clinics and physicians’ offices can utilize sentiment analysis and time-to-next-complaint methods to analyze web-based patient comments.

scholarly journals Analisis Sentimen Movie Review menggunakan Word2Vec dan metode LSTM Deep Learning

2021 ◽  
Vol 5 (3) ◽  
pp. 1018
Author(s):  
Widi Widayat
Keyword(s):  
Deep Learning ◽  
Sentiment Analysis ◽  
Average Length ◽  
Tuning Parameter ◽  
The Internet ◽  
Vector Representation ◽  
Text Documents ◽  
Text Data ◽  
Internet Users ◽  
Corpus Data

The increasing number of internet users is directly in line with the increasing number of data on the internet that is available for analysis, especially data in text form. The availability of this text data encourages a lot of sentiment analysis research. However, it turns out that the availability of abundant text data is also one of the challenges in sentiment analysis research. Datasets that consist of long and complex text documents require a different approach. In this study, LSTM was chosen to be used as a sentiment classification method. This research uses a movie review dataset that consists of 25,000 review documents, with an average length per review is 233 words. The research uses CBOW and Skip-Gram methods on word2vec to form a vector representation of each word (word vector) in the corpus data. Several dimensions of the word vector was used in this research, there are 50, 60, 100, 150, 200, and 500, this tuning parameter is used to determine their effect on the resulting accuracy. The best accuracy around 88.17% is obtained at the word vector 100 dimension and the lowest accuracy is 85.86% at the word vector 500 dimension.

scholarly journals LOSSLESS AND LOSSY IMAGE COMPRESSION BASED ON DATA FOLDING

2014 ◽  
pp. 45-49
Author(s):  
GAYATRI. B. TIGADI ◽  
MANJULADEVI T.H.
Keyword(s):  
Image Compression ◽  
Imaging Techniques ◽  
Region Of Interest ◽  
Lossless Compression ◽  
The Other ◽  
The Internet ◽  
Image Size ◽  
Using Data ◽  
Very High ◽  
Considerable Loss

Image compression plays a very important role in image processing especially when we have to send the image on the internet. Since imaging techniques produce prohibitive amounts of data, compression is necessary for storage and communication purposes. Many current compression schemes provide a very high compression rates but with considerable loss of quality. On the other hand, in some areas in medicine, it may be sufficient to maintain high image quality only in the region of interest, i.e., in diagnostically important regions called region of interest. In the proposed work images are compressed using Data folding technique which uses the property of adjacent neighbour redundancy for prediction. In this method first column folding is applied followed by the row folding iteratively till the image size reduces to predefined value, then arithmetic encoding is applied which results the compressed image at the end before transmitting the data. In this paper lossless compression is achieved only at the region of interest and it is mainly suitable for medical images.

Methods of Countering Cyber Recruitment (Iraq Model)

2019 ◽  
pp. 196
Author(s):  
Hind Mohammed Abdul Jabbar Ali
Keyword(s):  
Social Justice ◽  
Young People ◽  
Young Men ◽  
The Other ◽  
The Internet ◽  
Information Network ◽  
Political Repression ◽  
Electronic Information ◽  
Terrorist Organizations ◽  
Other Hand

Connecting to the  electronic information network (internet) became the most characteristic that distinguish this era However , the long hours which young men daily spend on the internet On the other hand ,there are many people who are waiting for the chance to talk and convince them with their views This will lead the young people to be part in the project of the “cyber armies “that involved with states and terrorist organizations  This project has been able  to recruitment hundreds of people every day to work in its rank . It is very difficult to control these websites because we can see the terrorist presence in all its forms in the internet   In addition there are many incubation environments that feed in particular the young people minds                                                                                         Because they are suffering from the lack of social justice Also the unemployment, deprivation , social and political repression So , that terrorist organizations can attract young people through the internet by convincing them to their views and ideas . So these organizations will enable to be more  stronger.

PERBANDINGAN METODE MD4 DAN SHA 384 UNTUK MENDETEKSI ORISINALITAS CITRA DIGITAL

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Lemcia Hutajulu ◽  
Hery Sunandar ◽  
Imam Saputra
Keyword(s):  
Digital Image ◽  
Detrimental Effect ◽  
Digital Images ◽  
Computer Crime ◽  
The Other ◽  
Image Manipulation ◽  
The Internet ◽  
Secret Key

Cryptography is used to protect the contents of information from anyone except those who have the authority or secret key to open information that has been encoded. Along with the development of technology and computers, the increase in computer crime has also increased, especially in image manipulation. There are many ways that people use to manipulate images that have a detrimental effect on others. The originality of a digital image is the authenticity of the image in terms of colors, shapes, objects and information without the slightest change from the other party. Nowadays many digital images circulating on the internet have been manipulated and even images have been used for material fraud in the competition, so we need a method that can detect the image is genuine or fake. In this study, the authors used the MD4 and SHA-384 methods to detect the originality of digital images, by using this method an image of doubtful authenticity can be found out that the image is authentic or fake.Keywords: Originality, Image, MD4 and SHA-384

Shalott’s Song: a Specific Feature Found in Balmont’s Translation of A. Tennyson’s Poem «The Lady of Shalott»

2020 ◽  
pp. 22-33
Author(s):  
Margarita Shanurina
Keyword(s):  
Neutral Word ◽  
Fairy Tale ◽  
The Other ◽  
Original Text ◽  
Academic Paper ◽  
Other Hand ◽  
The One

This academic paper is devoted to the analysis of a specific feature which could be found in K. Balmont’s translation of A. Tennyson’s poem «The Lady of Shalott». The aim of the work is to study the reasons why Balmont uses the word «волшебница» to describe the heroine in his translation while there is no word with such semantics in the original text. (This word is put in the name of the translated work and it is found in almost every stanza).English analogue of the word «volshebnitsa» (that is, the word «enchantress», which, according to the Oxford English Dictionary, is closest to this word in semantics), while in the original text of the poem this word is not mentioned, the neutral word «lady» is used andonce (in the speech of the mower who hears the heroine singing, but does not see her) there is the word «fairy». This article, on the one hand, summarizes existing studies on the topic; on the other hand, complements them. The study highlights and considers several reasons for the above-mentioned discrepancy between the original text and its translation: emphasizing the connection with a fairy tale, revealing a number of motifs which play an important role in the work of Balmont himself (namely, motifs of music and creativity as magic) and an indication of the main heroine’s charming beauty.

Deep Learning for text in limted data settings

2020 ◽  
Author(s):  
Pathikkumar Patel ◽  
Bhargav Lad ◽  
Jinan Fiaidhi
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Deep Learning ◽  
Sentiment Analysis ◽  
Transfer Learning ◽  
Text Classification ◽  
State Of The Art ◽  
Time Series Forecasting ◽  
Text Data ◽  
Performance Levels

During the last few years, RNN models have been extensively used and they have proven to be better for sequence and text data. RNNs have achieved state-of-the-art performance levels in several applications such as text classification, sequence to sequence modelling and time series forecasting. In this article we will review different Machine Learning and Deep Learning based approaches for text data and look at the results obtained from these methods. This work also explores the use of transfer learning in NLP and how it affects the performance of models on a specific application of sentiment analysis.

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.

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