Wyniki wyszukiwania - BazTech

1

Social media analysis of the public perception of urban vehicle access regulations

Ogunkunbi Gabriel, Meszaros Ferenc

Transport Problems

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2023

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T. 18, z. 1

157--168

EN

Heavy motorisation in the wake of increasing urbanisation is one of the significant transport problems cities face today. There are practical measures under the panoply of urban vehicle access regulations (UVARs) used to stimulate sustainable mobility behaviour changes in the urban population and reduce reliance on passenger car travel. However, the adoption and implementation of such measures are often riddled with challenges, particularly building public acceptability and preserving social justice. Overcoming these challenges will also require cities to understand how the mobility needs of residents change over time. Considering the limitations of conventional data-collection and monitoring approaches, this study explored and analysed the public perception of UVARs over 12 years through natural language processing techniques using social media as a data source. The results show that UVARs are a prominent topic in public discussion and that the average sentiment expressed in tweets tended to be more positive than negative, with a gradual increase observed over the 12-year study period. In addition, the patterns observed in the data and the topics modelled were consistent with the events and talking points in society related to UVARs. Hence, this study demonstrates that social media data can help policymakers assess public sentiments during the ideation, design, implementation, and operational phases of UVARs and other transport policy measures.

2

Insights into attitudes towards financial innovations by its users

Garškaitė-Milvydienė Kristina, Maknickienė Nijolė, Tvaronavičienė Manuela

Polish Journal of Management Studies

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2023

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Vol. 27, No. 2

106--119

EN

Significant technological advances have determined the importance of FinTech firms worldwide; they attract substantial investment and put competitive pressure on banks providing traditional services. The development of financial innovations challenges users accustomed to classical financial solutions since trust in financial technologies requires risk assessment, which becomes increasingly complicated. The main participants shaping the attitude towards FinTech are investors, customers, regulators, technology developers, and risk managers. The paper aims to explore FinTech opportunities and challenges, as the public understands them. The authors used scientific sources and employed big data processing methods to evaluate social media users' attitudes towards the FinTech sector. The obtained results revealed that, despite of overall positive attitude, FinTech companies have to pay special attention to investment management and ensuring the security and privacy of clients’ data.

PL

Znaczące postępy technologiczne zdeterminowały znaczenie firm FinTech na całym świecie; przyciągają znaczne inwestycje i wywierają presję konkurencyjną na banki świadczące tradycyjne usługi. Rozwój innowacji finansowych stanowi wyzwanie dla użytkowników przyzwyczajonych do klasycznych rozwiązań finansowych, ponieważ zaufanie do technologii finansowych wymaga oceny ryzyka, która staje się coraz bardziej skomplikowana. Głównymi uczestnikami kształtującymi podejście do FinTech są inwestorzy, klienci, organy regulacyjne, twórcy technologii i menedżerowie ryzyka. Artykuł ma na celu zbadanie możliwości i wyzwań FinTech, tak jak rozumie je opinia publiczna. Autorzy wykorzystali źródła naukowe i zastosowali metody przetwarzania dużych zbiorów danych, aby ocenić nastawienie użytkowników mediów społecznościowych do sektora FinTech. Uzyskane wyniki pokazały, że pomimo ogólnie pozytywnego nastawienia, firmy FinTech muszą zwracać szczególną uwagę na zarządzanie inwestycjami oraz zapewnienie bezpieczeństwa i prywatności danych klientów.

3

Trip planning mobile application: a perspective case study of user experience

Pawełoszek Ilona, Wieczorkowski Jędrzej

Engineering Management in Production and Services

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2023

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Vol. 15, no. 2

55--71

EN

Mobile trip planning applications may contribute to popularising public transport, provided they work efficiently and gain high user acceptance. This article aims to take a closer look at the functioning of the JakDojade application, which has been the most popular platform in Poland for several years, supporting travel planning by public transport. In the presented case study, the authors tried to diagnose problems and indicate the directions of application development. At the same time, through this analysis, the authors aimed to demonstrate the usefulness of researching user comments from the viewpoint of managing the development of mobile applications and related services. A case study methodology was used to perform a descriptive study. Data on user feedback on JakDojade mobile application in Poland comes from Google Play Store. Semantic categorisation of user comments and sentiment analysis allowed for identifying user problems and diagnosing emotions related to its use. The presented methodology allowed for diagnosing typical user problems for the JakDojade application, which may help indicate further development directions. The authors attempted to demonstrate the usefulness of researching user comments from the point of view of managing the development of mobile applications and related services. The semi-automatic approach to text analysis presented in the article highlights the problems related to the study of user reviews. The limitations of the proposed methodology and the possibilities for its improvement were indicated.

4

Handling dimensionality of ambiguity using ensemble classification in social networks to detect multi-label sentiment polarity

Sonawane Sudarshan S., Kolhe Satish R.

Computer Assisted Methods in Engineering and Science

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2023

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Vol. 30, no. 1

7--26

EN

With ever-increasing demand, social media platforms are rapidly developing to enable users to express and share their opinions on a variety of topics. Twitter is one such social media site. This platform enables a comprehensive view of the social media target setting, which may include products, social events, political scenarios, and administrative resolutions. The accessible tweets expressing the target audience’s perspective are frequently impacted by ambiguity caused by natural language processing (NLP) limitations. By classifying tweets according to their sentiment polarity, we can determine whether they express a good or negative point of view, a neutral opinion, or an input tweet that is irrelevant to the sentiment polarity context. Categorizing tweets according to their sentiment can assist future activities within the target domain in constructively evaluating the sentiment polarity and enabling improved decision-making based on the observed sentiment polarity. In this study, tweets that were previously categorized with one of the sentiment polarities were used to conduct predictive analytics of the new tweet to determine its sentiment polarity. The ambiguity of the tweets corpus utilized in the training phase is a critical limitation of the sentiment categorization procedure. While several recent models proposed sentiment classification algorithms, they confined themselves to two labels: positive and negative opinion, oblivious to the plague of ambiguity in the training corpus. In this regard, a novel multi-label classification of sentiment polarity called handling dimensionality of ambiguity using ensemble classification (HAD-EC) method, which diffuses ambiguity and thus minimizes false alerts, is proposed. The experimental assessment validates the HAD-EC approach by comparing the suggested model’s performance to other two existing models.

5

Project success and communication with stakeholders

Targiel Krzysztof S.

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2022

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z. 155

527--534

EN

Purpose: The aim of this paper is to analyze possibilities of using sentiment analysis in project management. Design/methodology/approach: The research methods used in the article were desk research analysis of available source data on the success of project. Then additional research was done on methods of sentiment analysis. Findings: During the course of this work was found a way of use sentiment analysis to improve project management. Research limitations/implications: The proposed idea necessitates research on the verification of the usefulness of the proposed indicators. Practical implications: The indicators proposed in the work have the potential to be used in the project management support application. Originality/value: Novelty of proposed paper are idea of two indicators for improvement project management

6

An evaluation of machine learning and latent semantic analysis in text sentiment classification

Miazga Justyna, Hachaj Tomasz

Technical Transactions

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2020

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Vol. 117, iss. 1

art. no. e2020030

EN

In this paper, we compare the following machine learning methods as classifiers for sentiment analysis: k – nearest neighbours (kNN), artificial neural network (ANN), support vector machine (SVM), random forest. We used a dataset containing 5,000 movie reviews in which 2,500 were marked as positive and 2,500 as negative. We chose 5,189 words which have an influence on sentence sentiment. The dataset was prepared using a term document matrix (TDM) and classical multidimensional scaling (MDS). This is the first time that TDM and MDS have been used to choose the characteristics of text in sentiment analysis. In this case, we decided to examine different indicators of the specific classifier, such as kernel type for SVM and neighbour count in kNN. All calculations were performed in the R language, in the program R Studio v 3.5.2. Our work can be reproduced because all of our data sets and source code are public.

7

Languages' impact on emotional classification methods

Eilertsen Alexander C., Højbjerg Rose Dennis, Langballe Erichsen Peter, Engesgaard Christensen Rasmus, Pratap Deb Nath Rudra

Annals of Computer Science and Information Systems

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2019

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Vol. 18

277--286

EN

There is currently a lack of research concerning whether Emotional Classification (EC) research on a language is applicable to other languages. If this is the case then we can greatly reduce the amount of research needed for different languages. Therefore, we propose a framework to answer the following null hypothesis: The change in classification accuracy for Emotional Classification caused by changing a single preprocessor or classifier is independent of the target language within a significance level of p = 0.05. We test this hypothesis using an English and a Danish data set, and the classification algorithms: Support-Vector Machine, Naive Bayes, and Random Forest. From our statistical test, we got a p-value of 0.12852 and could therefore not reject our hypothesis. Thus, our hypothesis could still be true. More research is therefore needed within the field of cross-language EC in order to benefit EC for different languages.

8

Customer product review summarization over time for competitive intelligence

Amarouche Kamal, Benbrahim Houda, Kassou Ismail

Journal of Automation Mobile Robotics and Intelligent Systems

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2018

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Vol. 12, No. 4

70--82

EN

Nowadays, Customer’s product reviews can be widely found on the Web, be it in personal blogs, forums, or ecommerce websites. They contain important products’ information and therefore became a new data source for competitive intelligence. On that account, these reviews need to be analyzed and summarized in order to help the leader of an entity (company, brand, etc.) to make appropriate decisions in an efective way. However, most previous review summarization studies focus on summarizing sentiment distribution toward different product features without taking into account that the real advantages and disadvantages of a product clarify over time. For this reason, in this work we aim to propose a new system for product opinion summarization which depends on the time when reviews are expressed and that covers the sentiments change about product features. The proposed system firstly, generates a summary based on product features in order to give more accurate and efficient information about different features. secondly, classify the product based on its features in its appropriate class (good, medium or bad product) using a fuzzy logic system. The experimental results demonstrate the effectiveness of the proposed system to generate the real image of a product and its features in reviews.