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Wyniki wyszukiwania dla: sentiment analysis

Wyniki wyszukiwania dla: sentiment analysis

  • Sentiment Analysis of Facebook Posts:the Uber case

    Publikacja

    - Rok 2017

    This article analyses the sentiment of opinions, i. e. its classification as phrases with a neutral, positive and negative emotional tone. Data used as a basis for the analysis were opinions expressed by Facebook users about Uber and collected in the period between July 2016 and July 2017. The primary objective of the study was to obtain information about the perceptions of Uber over thirteen consecutive months. The study confirms...

  • SACAM A Model for Describing and Classifying Sentiment Analysis Methods

    Publikacja

    In this paper we introduce SACAM — a model for describing and classifying sentiment analysis (SA) methods. The model focuses on the knowledge used during processing textual opinions. SACAM was designed to create informative descriptions of SA methods (or classes of SA methods) and is strongly integrated with its accompanying graphical notation suited for presenting the descriptions in diagrammatical form. The paper discusses applications...

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  • Migrants vs. stayers in the pandemic – A sentiment analysis of Twitter content

    Publikacja
    • O. Czeranowska
    • K. Chlasta
    • P. Miłkowski
    • I. Grabowska
    • J. Kocoń
    • K. Hwaszcz
    • J. Wieczorek
    • A. Jastrzębowska

    - Telematics and Informatics Reports - Rok 2023

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  • Business Sentiment Analysis. Concept and Method for Perceived Anticipated Effort Identification

    Publikacja

    - Rok 2019

    Representing a valuable human-computer interaction interface, Sentiment Analysis (SA) is applied to a wide range of problems. In the present paper, the researchers introduce a novel concept of Business Sentiment (BS) as a measurement of a Perceived Anticipated Effort (PAE) in the context of business processes (BPs). BS is considered as an emotional component of BP task contextual complexity perceived by a process worker after reading...

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  • Examining Government-Citizen Interactions on Twitter using Visual and Sentiment Analysis

    Publikacja

    - Rok 2018

    The goal of this paper is to propose a methodology comprising a range of visualization techniques to analyze the interactions between government and citizens on the issues of public concern taking place on Twitter, mainly through the official government or ministry accounts. The methodology addresses: 1) the level of government activity in different countries and sectors; 2) the topics that are addressed through such activities;...

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  • Mobile operators at war: opinion mining and sentiment analysis on social media

    Publikacja

    Considering hermetic and very competitive market such as mobile operator ones, social media has become best alternative for contact with customer and gathering data and opinions. Different style of running social media profiles is giving different results. The research presented in this paper aims to show the number of responses gathered from polish Internet users and its sentiment for mobile operator brands. It also presents practical...

  • Evaluation of a company’s image on social media using the Net Sentiment Rate

    Publikacja

    - Rok 2020

    Vast amounts of new types of data are constantly being created as a result of dynamic digitization in all areas of our lives. One of the most important and valuable categories for business is data from social networks such as Facebook. Feedback resulting from the sharing of thoughts and emotions, expressed in comments on various products and services, is becoming the key factor on which modern business is based. This feedback is...

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  • Improving the Accuracy in Sentiment Classification in the Light of Modelling the Latent Semantic Relations

    Publikacja

    - Information - Rok 2018

    The research presents the methodology of improving the accuracy in sentiment classification in the light of modelling the latent semantic relations (LSR). The objective of this methodology is to find ways of eliminating the limitations of the discriminant and probabilistic methods for LSR revealing and customizing the sentiment classification process (SCP) to the more accurate recognition of text tonality. This objective was achieved...

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  • Nina Rizun dr

    Nina Rizun jest adiunktem na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej. W  październiku 1999 r. uzyskała stopień doktora nauk technicznych za specjalizacją Gospodarka przedsiębiorstwa i organizacja produkcji. W latach 1993–2000 pracowała na Wydziale Informatyki Ekonomicznej w Akademji Metalurgicznej, Dnipro, Ukraina. W latach 2000–2016 – na Wydziale Cybernetyki Ekonomicznej i Metod Matematycznych na Uniwersytecie Alfreda...

  • Methodology for Text Classification using Manually Created Corpora-based Sentiment Dictionary

    Publikacja

    - Rok 2018

    This paper presents the methodology of Textual Content Classification, which is based on a combination of algorithms: preliminary formation of a contextual framework for the texts in particular problem area; manual creation of the Hierarchical Sentiment Dictionary (HSD) on the basis of a topically-oriented Corpus; tonality texts recognition via using HSD for analysing the documents as a collection of topically completed fragments...

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  • Celebrities’ personal brand authenticity in social media: an application in the context of football top-players. The Robert Lewandowski case

    Publikacja

    - Rok 2018

    The aim of the study is to explore personal brand authenticity in social media through sentiment analysis. A survey has been conducted in the context of football players with respect to Robert Lewandowski – the most valuable Polish football-celebrity brand. Authors first assess antecedents of his brand authenticity basing on an international sample of social media users, made of 219 cases from 22 countries (intentionally excluding...

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  • Personal Brand Value and Social Media, the Top Football Players’ Case

    Publikacja

    - Rok 2018

    Personal branding valuation and social media usage are new and empirically unexplored areas of research. The aim of the presented study is to determine how social media performance and sentiment are related to the value of a personal brand. Based on an example of 100 most valuable football players, in reference to transfermarkt.com and the sentione.com (sentiment analysis), the author points out the strongest...

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  • Analysis of results of large-scale multimodal biometric identity verification experiment

    An analysis of a large set of biometric data obtained during the enrolment and the verification phase in an experimental biometric system installed in bank branches is presented. Subjective opinions of bank clients and of bank tellers were also surveyed concerning the studied biometric methods in order to discover and to explore relations emerging from the obtained multimodal dataset. First, data acquisition and identity verification...

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  • Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers

    Publikacja
    • T. Shmelova
    • Y. Sikirda
    • N. Rizun
    • V. Lazorenko
    • V. Kharchenko

    - Rok 2020

    This chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...

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  • The Impact of Lexicon Adaptation on the Emotion Mining From Software Engineering Artifacts

    Publikacja

    - IEEE Access - Rok 2020

    Sentiment analysis and emotion mining techniques are increasingly being used in the field of software engineering. However, the experiments conducted so far have not yielded high accuracy results. Researchers indicate a lack of adaptation of the methods of emotion mining to the specific context of the domain as the main cause of this situation. The article describes research aimed at examining whether the adaptation of the lexicon...

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  • Introduction to the special issue on machine learning in acoustics

    Publikacja
    • Z. Michalopoulou
    • P. Gerstoft
    • B. Kostek
    • M. A. Roch

    - Journal of the Acoustical Society of America - Rok 2021

    When we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...

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  • Analiza sentymentu jako narzędzie monitorowania wyników finansowych przedsiębiorstwa

    Media społecznościowe tworzą globalną platformę do dzielenia się interesującymi pomysłami lub nowościami, komentarzami i recenzjami. Stanowią bogate źródło danych do eksploracji opinii w celu pozyskania wcześniej nieznanej i użytecznej wiedzy biznesowej, która umożliwi nie tylko zwinne zarządzanie na rzecz skutecznej obsługi klienta, ale również powinna mieć odzwierciedlenie w finansowych wynikach przedsiębiorstwa. Za główny cel...

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  • Anna Baj-Rogowska dr

    Anna Baj-Rogowska zatrudniona jest na stanowisku adiunkta w Katedrze Informatyki w Zarządzaniu (Politechnika Gdańska, Wydział Zarządzania i Ekonomii). Jej wyższa edukacja związana jest z Uniwersytetem Gdańskim, gdzie ukończyła magisterskie studia informatyczne, studia doktoranckie i następnie uzyskała stopień naukowy doktora nauk ekonomicznych w zakresie nauk o zarządzaniu (Katedra Informatyki Ekonomicznej na Wydziale Zarządzania...

  • Audio-visual aspect of the Lombard effect and comparison with recordings depicting emotional states.

    In this paper an analysis of audio-visual recordings of the Lombard effect is shown. First, audio signal is analyzed indicating the presence of this phenomenon in the recorded sessions. The principal aim, however, was to discuss problems related to extracting differences caused by the Lombard effect, present in the video , i.e. visible as tension and work of facial muscles aligned to an increase in the intensity of the articulated...

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  • Towards semantic-rich word embeddings

    Publikacja

    - Annals of Computer Science and Information Systems - Rok 2019

    In recent years, word embeddings have been shown to improve the performance in NLP tasks such as syntactic parsing or sentiment analysis. While useful, they are problematic in representing ambiguous words with multiple meanings, since they keep a single representation for each word in the vocabulary. Constructing separate embeddings for meanings of ambiguous words could be useful for solving the Word Sense Disambiguation (WSD)...

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  • Do online reviews reveal mobile application usability and user experience? The case of WhatsApp

    The variety of hardware devices and the diversity of their users imposes new requirements and expectations on designers and developers of mobile applications (apps). While the Internet has enabled new forms of communication platform, online stores provide the ability to review apps. These informal online app reviews have become a viral form of electronic wordof-mouth (eWOM), covering a plethora of issues. In our study, we set ourselves...

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  • Text Mining Algorithms for Extracting Brand Knowledge; The fashion Industry Case

    Publikacja

    - Rok 2018

    Brand knowledge is determined by customer knowledge. The opportunity to develop brands based on customer knowledge management has never been greater. Social media as a set of leading communication platforms enable peer to peer interplays between customers and brands. A large stream of such interactions is a great source of information which, when thoroughly analyzed, can become a source of innovation and lead to competitive advantage....

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  • Analyzing and Visualizing Government-Citizen Interactions on Twitter to Support Public Policy-making

    Publikacja

    - Digital Government: Research and Practice - Rok 2020

    Twitter is widely adopted by governments to communicate with citizens. It has become a major source of data for analyzing how governments communicate with citizens and how citizens respond to such communication, uncovering important insights about government-citizen interactions that could be used to support public policy-making. This article presents research that aims at developing a software tool called Twitter Analytics for...

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  • The image of the City on social media: A comparative study using “Big Data” and “Small Data” methods in the Tri-City Region in Poland

    Publikacja

    “The Image of the City” by Kevin Lynch is a landmark planning theory of lasting influence; its scientific rigor and relevance in the digital age were in dispute. The rise of social media and other digital technologies offers new opportunities to study the perception of urban environments. Questions remain as to whether social media analytics can provide a reliable measure of perceived city images? If yes, what implication does...

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  • Exploring the Usability and User Experience of Social Media Apps through a Text Mining Approach

    This study aims to evaluate the applicability of a text mining approach for extracting UUX-related issues from a dataset of user comments and not to evaluate the Instagram (IG) app. This study analyses textual data mined from reviews in English written by IG mobile application users. The article’s authors used text mining (based on the LDA algorithm) to identify the main UUX-related topics. Next, they mapped the identified topics...

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  • Contextual ontology for tonality assessment

    classification tasks. The discussion focuses on two important research hypotheses: (1) whether it is possible to construct such an ontology from a corpus of textual document, and (2) whether it is possible and beneficial to use inferencing from this ontology to support the process of sentiment classification. To support the first hypothesis we present a method of extraction of hierarchy of contexts from a set of textual documents...

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  • Multi-Criteria Knowledge-Based Recommender System for Decision Support in Complex Business Processes

    Publikacja

    - Rok 2019

    In this paper, we present a concept of a multi-criteria knowledge-based Recommender System (RS) designed to provide decision support in complex business process (BP) scenarios. The developed approach is based on the knowledge aspects of Stylistic Patterns, Business Sentiment and Decision-Making Logic extracted from the BP unstructured texts. This knowledge serves as an input for a multi-criteria RS algorithm. The output is prediction...

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  • Web Questionnaire as Construction Method of Affect-annotated Lexicon - Risks Reduction Strategy

    Publikacja

    - Rok 2015

    The paper concerns credibility of construction methods for affect-annotated lexicons, specifically a web questionnaire is explored and evaluated. Web-based surveys are susceptible to some risks, which might influence credibility of the results, as some participants might perform random clicks or intentionally falsify the responses. The paper explores the risks and proposes some strategies to reduce them. The strategies are supported...

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