scholarly journals Sentiment Analysis-Enhancements and Applications

2021 ◽  
Vol 10 (4) ◽  
pp. 56-70
Author(s):  
Aayush Gupta ◽  
◽  
Anant Gandhi ◽  
Saarthak Agarwal ◽  
Shamin Chokshi ◽  
...  
Keyword(s):  
Sentiment Analysis ◽  
Customer Service ◽  
Language Processing ◽  
Semantic Analysis ◽  
Point Of View ◽  
Market Survey ◽  
Specific Subject ◽  
Domain Specific ◽  
The Subject ◽  
The Voice

The concept of Natural Language Processing that deals with problems of identifying the sentiment from the voice or text of a speaker or writer and then use that analysis further for making predictions, market survey, customer service, product satisfaction, precision targeting etc. is called Sentiment analysis. From one viewpoint, it is an abstract evaluation of something dependent on close to home observational experience. It Is mostly established in target realities and incompletely governed by feelings. Then again, a sentiment can be deciphered as a kind of measurement in the information in regards to a specific subject. It is a lot of markers that mix present a point of view, i.e., perspective for the specific issue. So as to enhance the accuracy of sentiment analysis/classification, it is imperative to appropriately recognize the semantic connections between the various words and phrases that are describing the subject or aspect. This can be done by applying semantic analysis with a syntactic parser and supposition vocabulary. This research will discuss different sets of approaches for application or domain specific problems and then compare them to obtain the best possible approaches to the problem of sentiment analysis.

scholarly journals A Design on Bank Customer Complaints Analysis using Natural Language Processing

2019 ◽  
Vol 9 (2S) ◽  
pp. 522-525
Keyword(s):  
Sentiment Analysis ◽  
Customer Service ◽  
Language Processing ◽  
Banking Sector ◽  
Customer Segmentation ◽  
Business Leaders ◽  
Customer Complaints ◽  
Client Care ◽  
Voice Of Customer ◽  
The Voice

The banking sector has undergone a major revolution with the advent of digital transformation. The entry of Fintech and tech giants such as Google, Amazon, and Facebook have introduced convenient banking that is easy to understand and use. In this focused condition, banks are understanding the significance of client care and fulfillment and need to give close consideration to the Voice of Customer to improve client experience. By dissecting and getting bits of knowledge from client input, banks will have better data to settle on key choices. In their quest to better understand their customers, banks are seeking artificial intelligence (AI) solutions in the form the of sentiment analysis. What is sentiment analysis? In simple words, sentiment analysis is the process of detecting a customer’s reaction to a product, brand, situation or event through texts, posts, reviews, and other digital content. Using sentiment analysis, business leaders can gain deep insight into how their customers think and feel. The analysis can help in tracking customer opinions over a period of time, determine customer segmentation, plan product improvements, prioritize customer service issues, and many more business use cases

scholarly journals State of Art for Semantic Analysis of Natural Language Processing

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Dastan Hussen Maulud ◽  
Subhi R. M. Zeebaree ◽  
Karwan Jacksi ◽  
Mohammed A. Mohammed Sadeeq ◽  
Karzan Hussein Sharif
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Prediction Error ◽  
Semantic Analysis ◽  
Essential Feature ◽  
Semantic Interpretation ◽  
The Subject ◽  
State Of Art

Semantic analysis is an essential feature of the NLP approach. It indicates, in the appropriate format, the context of a sentence or paragraph. Semantics is about language significance study. The vocabulary used conveys the importance of the subject because of the interrelationship between linguistic classes. In this article, semantic interpretation is carried out in the area of Natural Language Processing. The findings suggest that the best-achieved accuracy of checked papers and those who relied on the Sentiment Analysis approach and the prediction error is minimal.

State of Art for Semantic Analysis of Natural Language Processing

2021 ◽  
Vol 1 (2) ◽  
pp. 21-28
Author(s):  
Dastan Hussen Maulud ◽  
Subhi R. M. Zeebaree ◽  
Karwan Jacksi ◽  
Mohammed Mohammed Sadeeq ◽  
Karzan Hussein Sharif
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Prediction Error ◽  
Semantic Analysis ◽  
Essential Feature ◽  
Semantic Interpretation ◽  
The Subject ◽  
State Of Art

Semantic analysis is an essential feature of the NLP approach. It indicates, in the appropriate format, the context of a sentence or paragraph. Semantics is about language significance study. The vocabulary used conveys the importance of the subject because of the interrelationship between linguistic classes. In this article, semantic interpretation is carried out in the area of Natural Language Processing. The findings suggest that the best-achieved accuracy of checked papers and those who relied on the Sentiment Analysis approach and the prediction error is minimal.

Discovery of Sustainable Transport Modes Underlying TripAdvisor Reviews With Sentiment Analysis

2021 ◽  
pp. 180-199
Author(s):  
Ainhoa Serna ◽  
Jon Kepa Gerrikagoitia
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Predictive Analytics ◽  
Data Gathering ◽  
Point Of View ◽  
Training Data ◽  
Complete Analysis ◽  
Sustainable Transport ◽  
Transport Modes

In recent years, digital technology and research methods have developed natural language processing for better understanding consumers and what they share in social media. There are hardly any studies in transportation analysis with TripAdvisor, and moreover, there is not a complete analysis from the point of view of sentiment analysis. The aim of study is to investigate and discover the presence of sustainable transport modes underlying in non-categorized TripAdvisor texts, such as walking mobility in order to impact positively in public services and businesses. The methodology follows a quantitative and qualitative approach based on knowledge discovery techniques. Thus, data gathering, normalization, classification, polarity analysis, and labelling tasks have been carried out to obtain sentiment labelled training data set in the transport domain as a valuable contribution for predictive analytics. This research has allowed the authors to discover sustainable transport modes underlying the texts, focused on walking mobility but extensible to other means of transport and social media sources.

scholarly journals Sentiment analysis of social media content in Croatian health industry

2021 ◽  
Vol 9 (1) ◽  
pp. 37-57
Author(s):  
Jelena Mušanović ◽  
Jelena Dorčić ◽  
Tea Baldigara
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Modern Society ◽  
Essential Elements ◽  
Point Of View ◽  
Daily Routine ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality ◽  
Facebook Pages

While social media have become a daily routine in modern society, brand communication and engagement with customers have become essential elements of marketing strategy and success in the tourism and hotel industry. This revolution of social media, in tourism and hospitality marketing, contributed to the rise of a novel sentiment analysis from a machine learning and natural language processing point of view. The purpose of the study is: to provide a general descriptive overview of comments posted by Facebook page followers; to identify specific textual attributes of hotel brand posts on social media and to apply the sentiment analysis to Facebook comments from four- and five-star hotel brands in Croatia to identify and compare customers’ feelings and attitudes towards the staff, services and products that hotel brands promote by posting messages on Facebook pages. To analyse hotel brand sentiments, the authors collected a total of 4,248 comments and 2,373 postings in English, German and Italian. The results showed that the comments on four- and five-star hotel brands expressed predominantly positive sentiments. Despite the positively oriented sentiments in the comments, Facebook page followers are predominantly passive users and do not tend to comment actively. The results can be used by marketers in the tourism and hospitality industry to plan their future social media communication strategies.

scholarly journals Investigating the role of Word Embeddings in sentiment analysis

2020 ◽  
pp. 18-24
Author(s):  
Samuele Martinelli ◽  
Gloria Gonella ◽  
Dario Bertolino
Keyword(s):  
Sentiment Analysis ◽  
Customer Service ◽  
Language Processing ◽  
Question Answering ◽  
Classification Task ◽  
Mining Machine ◽  
Computational Techniques ◽  
Human Language ◽  
Simple Classification ◽  
Learning Techniques

During decades, Natural language processing (NLP) expanded its range of tasks, from document classification to automatic text summarization, sentiment analysis, text mining, machine translation, automatic question answering and others. In 2018, T. Young described NLP as a theory-motivated range of computational techniques for the automatic analysis and representation of human language. Outside and before AI, human language has been studied by specialists from various disciplines: linguistics, philosophy, logic, psychology. The aim of this work is to build a neural network to perform a sentiment analysis on Italian reviews from the chatbot customer service. Sentiment analysis is a data mining process which identifies and extracts subjective information from text. It could help to understand the social sentiment of clients, respect a business product or service. It could be a simple classification task that analyses a sentence and tells whether the underlying sentiment is positive or negative. The potentiality of deep learning techniques made this simple classification task evolve, creating new, more complex sentiment analysis, e.g. Intent Analysis and Contextual Semantic Search.

scholarly journals Mutual sentiment

2020 ◽  
Vol 210 ◽  
pp. 15006
Author(s):  
Olga Maksimenko ◽  
Tatiana Semina ◽  
Alexander Khmelev ◽  
Natalia Dmitrieva
Keyword(s):  
Natural Language Processing ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Opinion Mining ◽  
Source Material ◽  
Affective States ◽  
Named Entities ◽  
Proper Nouns ◽  
The Subject ◽  
And Linguistics

Sentiment analysis is a modern task in natural language processing and linguistics. Also referred to as opinion mining, it deals with different kinds of affective states: opinion, emotions, stance and evaluations. Sentiment itself is the polarity of these affective states. Taking analytical articles as source material for the study, several problems should be considered. Firstly, these texts broaden the understanding of the subject of opinion, because it does not coincide with the author of the text in the majority of cases. Secondly, subjects and objects of opinion are entities – words or word combinations with strictly denoted referent. In the paper only Named Entities, that are normally expressed by proper nouns, are considered. This kind of sentiment analysis requires deeper research of possible sentiment relations between entities and of lexical and grammatical influence on these relations. The paper is devoted to the study of the influence of the group of lexemes on opinion structure. The research shows that mutual sentiment can be presented as stable patterns.

Sentiment Analysis Techniques, Tools, Applications, and Challenge

2020 ◽  
pp. 35-48
Author(s):  
Chitra A. Dhawale ◽  
Vandana V. Chaudhari
Keyword(s):  
Natural Language ◽  
Sentiment Analysis ◽  
Customer Service ◽  
Computational Linguistics ◽  
Language Processing ◽  
Marketing Research ◽  
Research Direction ◽  
Future Research ◽  
Source Materials

Sentiment (opinion) refers to the feelings of a human being, which are generally reflected through speech and writing in a particular natural language. The analysis of these sentiments are therefore carried with the help of natural language processing, text analysis, and computational linguistics to identify and extract subjective information in source materials. Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. Sentiment analysis is widely applied to reviews and social media for a variety of applications, ranging from marketing research, political reviews, policy making, decision making, customer service, etc. In this chapter the authors include the introduction to sentiment analysis, various approaches for classification of sentiment analysis, various tools used, the application areas, challenges, and future research direction in this most demanding area.

On the Acousmatics of Enunciation: Back to the Suture

2020 ◽  
Author(s):  
Sulgi Lie
Keyword(s):  
Point Of View ◽  
Social Dimension ◽  
The Political ◽  
Mirror Stage ◽  
The Gaze ◽  
Objet Petit A ◽  
Political Aesthetics ◽  
The Subject ◽  
Lacanian Theory ◽  
The Voice

With Kaja Silverman’s works, a reversal within Lacanian theory becomes abundantly clear that turns away from the old identification paradigm of imaginary misjudgement in the mirror stage. Following Lacan’s reformulation of the gaze as an “objet petit a,” the gaze is thought of as divided from the subject and placed on the side of the object. In the synthesis of Copjec’s/Žižek’s work with Michel Chion’s theories of voice and sound, my aim is to conceive of a fundamental acousmatics of film: not only the voice, but also the gaze in film is structurally acousmatic. In Lacan’s understanding, gaze and voice are strictly equivalent objects. As such, it is my intention to conceive of a political aesthetics from a psychoanalytic acousmatics of film. In the point-of-view paradoxes and transsubjective gazes in Rossellini’s and Antonioni’s post-neorealist films, I analyze the political and social dimension of this acousmatics.

scholarly journals The Attributive Features of the Hero as a Category of Musical Poetics in Pieces from the Children’s Musical Repertoire

ICONI ◽  
2019 ◽  
pp. 10-26
Author(s):  
Rimma M. Baikieva ◽  
Keyword(s):  
Performance Practice ◽  
Subject Matter ◽  
Semantic Analysis ◽  
Point Of View ◽  
Human Being ◽  
Analytical Aspect ◽  
The World ◽  
The Subject ◽  
Living Nature

The article offers means of defining the features of the hero as a structure of the musical text of pieces from the children’s repertoire. Since any kind of artistic text is created in accordance with unified semantics-bearing laws, the category of the musical hero is examined along with such categories of poetics as the author, the protagonist, the image, the dialogue, the scene, the subject matter, the idea, which, nonetheless, up to now have continued to be relegated to the sphere of metaphors. Nonetheless, the description of the features of the hero on the basis of intonational lexis of various types of etymology is seen as presenting its result. Demonstration of the indicated features incorporates a particular mechanism of semantic analysis, which makes it possible to elucidate the lexical structures manifesting the hero. Semantic analysis has shown that the category of the hero is presented in the musical text structurally; it may be described both as a biologically definite being and a socially concrete personality. Moreover, pieces from the children’s repertoire are endowed with the capacity of manifesting the personified hero who represents living nature. The attributing of the hero also sees the participation of the heading, which, nonetheless, does not always indicate the hero directly. However, the heading always (whether directly or indirectly) depicts the hero’s place of action and the world surrounding him.The hero receives his attribution most often in musical speech and in plastic models. Besides the “audible” and “visible” attributes, the hero in an artistic text is also actualized through the features of evaluative character: with their help the author, who is situated “off-screen,” endows the hero with the biological and characterological features of a human being. Study of musical content from the point of view of the categories of musical poetics may make the interaction of the analytical aspect with performance practice more effectual and productive. At the same time, the various approaches to the art of performance shall inevitably acquire new features which bring the performer’s activities in the questions of articulation and intonation closer with dramatic art.

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