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Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2026/r/gumushane/12260
  Financial literacy and psychological vulnerability to financial exploitation: the roles of financial anxiety, self-confidence, and behavior

  Çam, Alper Veli; Soydaş, Şafak Sönmez; Özbek, Adem; Çam, Handan

  Background: Financial exploitation constitutes a significant psychological vulnerability shaped by cognitive resources, emotional regulation, and financial decision-making behaviors. While financial literacy is widely recognized as a protective factor, limited empirical evidence disentangles the distinct psychological roles of financial knowledge, attitudes, and behaviors in reducing vulnerability to financial exploitation. Methods: This cross-sectional study analyzed survey data from 565 adults in Türkiye. Financial literacy was conceptualized as a multidimensional construct comprising financial knowledge, financial attitude, and financial behavior. Vulnerability to financial exploitation was assessed through three psychosocial indicators: self-confidence, financial anxiety, and financial satisfaction. Structural Equation Modeling (SEM) was employed to examine the relationships among cognitive, behavioral, and emotional components. Results: Financial knowledge was significantly associated with lower financial anxiety and higher financial satisfaction but showed no direct effect on self-confidence. Financial behavior emerged as the most robust protective factor, significantly enhancing self-confidence and financial satisfaction while substantially reducing financial anxiety. Financial attitude was positively related to financial satisfaction but did not significantly influence anxiety or self-confidence. Financial anxiety demonstrated a strong negative association with both self-confidence and financial satisfaction. Conclusions: Financial exploitation vulnerability is driven by interconnected psychological mechanisms rather than cognitive factors alone. The findings highlight the central role of behavior-based financial competencies and emotional regulation in strengthening financial resilience. Interventions aimed at preventing financial exploitation should prioritize behavioral skill development and psychological risk screening alongside traditional financial education approaches.

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• MakaleAçık Erişim2025/r/gumushane/16716
  Investigation of Fluctuations in Cryptocurrency Transactions with Sentiment Analysis

  Demírel, Ugur; Çam, Handan

  This study investigates public sentiment about popular cryptocurrencies listed on crypto exchanges in Turkey, using comments shared on social media platforms and online forums. The research seeks to enhance the existing body of knowledge by overcoming the shortcomings of sentiment analysis studies focused on Turkish texts. Data collected from social media and online forums were examined with sentiment analysis techniques. A total of 607,592 comments were analyzed, of which 89,986 were classified as negative, 72,655 as positive, and 444,951 as neutral. For binary classification, 89,986 negative and 72,655 positive examples were selected and machine-learning models were trained and tested on 162,641 examples. The study's methodology includes an in-depth examination of sentiment analysis results obtained using machine learning classifiers. The findings show how various cryptocurrencies are perceived on different social media platforms. For instance, BTC (Bitcoin) is generally perceived negatively on Investing.com and Telegram, while ETH (Ethereum) generally displays more negative views. These results help investors understand their perceptions and market expectations towards cryptocurrencies. This study deepens the role of social media sentiment analysis in cryptocurrency markets, contributing to the development of new methods and approaches for future research.

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• MakaleAçık Erişim2025/r/gumushane/13438
  In-depth review of industry 4.0: research implications and future perspectives; [Endüstri 4.0'ın derinlemesine incelemesi: araştırma sonuçları ve gelecek perspektifleri]

  Gurcan, Fatih; Cam, Handan; Ahmed, Sana

  The term “Industry 4.0” signifies a pivotal stage in industrial development, representing the current wave of transformation characterized by the integration of digital technologies into manufacturing and business processes. This concept spans multiple disciplines, including industrial engineering, data science, marketing, and strategic management. While a considerable volume of research has been conducted under the umbrella of Industry 4.0, there remains a lack of a comprehensive synthesis that captures the full scope and evolution of the field. The objective of this study is to systematically analyze, classify, and evaluate published research related to Industry 4.0, while identifying key gaps and forecasting potential future research directions. To accomplish this, a total of 10,696 journal articles indexed in the SCOPUS database from 2013 to 2023 were analyzed. The Latent Dirichlet Allocation (LDA) algorithm—a widely used probabilistic topic modeling technique in text mining—was applied to uncover latent themes within the literature. The analysis revealed 41 major topics, which were subsequently organized into five overarching categories: Sustainability, Manufacturing, Technology, Process, and Management. Findings indicate a notable shift in research emphasis over the past decade—from predominantly technical and engineering-focused issues toward broader concerns involving process optimization and organizational management. This transition highlights the growing importance of interdisciplinary approaches in addressing the complex challenges posed by Industry 4.0. Ultimately, this study not only maps the intellectual structure of existing research but also serves as a valuable resource for scholars, helping to navigate emerging trends and target underexplored areas in future investigations. This comprehensive thematic overview supports academics in pinpointing neglected subject areas, aligning future investigations with emerging priorities, and refining the strategic focus of Industry 4.0 research agendas.

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• MakaleAçık Erişim2025/r/gumushane/12524
  Investigation of the impact of instagram access restriction on individuals' psychological well-being, social and cultural perceptions, and adaptation strategies

  Özen, Üstün; Çam, Handan; İpkin, Metin; Kaldırımcı, Şahin Göktuğ

  This study comprehensively examines the psychological impacts of the Instagram access ban implemented in Turkey between August 2, 2024, and August 10, 2024, how these impacts are reflected in social consequences and cultural perceptions, and also assesses the adaptation strategies that individuals develop in response to the ban. Data were collected from 80 participants residing in Erzurum through online surveys and analyzed using MAXQDA 24 software. The findings suggest that the access ban had various psychological effects, with some participants experiencing changes in their social relationships and difficulties in accessing information. The impacts on social bonds and solidarity varied among participants, with some cases showing intensified social interactions. In terms of cultural perceptions, changes were observed in individuals' views on freedom and expression rights. The study provides important insights into how social media access bans can influence individual perceptions and social structures, suggesting that these findings could contribute to shaping social media policies.

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• Kitap BölümüYalnız künye2025/r/gumushane/11763
  Sentiment analysis of twitter data for US airlines' finance

  Cam, Handan; Demirel, Ugur

  The airline industry significantly promotes cultural, social, and financial globalization by facilitating connections between nations and individuals. Airline finance encompasses the intricate aspects of managing the economic, operational, and strategic elements of airline corporations on a global scale. In this industry, it is necessary to address various factors, including revenue management, risk management, cost control, and market competition. The interaction of these factors in the global aviation sector influences the financial situation of airlines, requiring strategic planning, flexibility, and a complete understanding of market dynamics. Sentiment analysis in aviation finance uses text and data mining techniques to examine emotional elements derived from social networks, consumer feedback, and news. This facilitates understanding consumer preferences, new trends, investment opportunities, risks, and marketing strategies. Sentiment analysis also helps manage brand reputation by monitoring sentiments expressed by passengers and the general public, allowing proactive measures to maintain a positive reputation. Airline companies rely on conventional customer feedback forms, which can be extremely laborious and timeconsuming. Twitter data is valuable for collecting consumer feedback tweets and conducting sentiment analysis. In this paper, we work on a dataset comprising tweets from the top major US airlines and perform a sentiment analysis in airline finance that can be used more efficiently and effectively in decision-making processes. This would allow airlines to adopt a more knowledgeable, targeted, and competitive strategy by understanding and assessing emotional context.

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• MakaleAçık Erişim2024/r/gumushane/20132
  Analysis of customer reviews for digital banking applications with text mining methods

  Çam, Handan; Sayin Okatan, Burcu

  Virtual services, which provide an important comfort area in today's digital world, are used by the majority of people. Accordingly, digital banking is one of the most used online financial services. In this research, it was aimed to analyze the digital banking services used by bank customers at a high rate and by using text mining methods using a data pool consisting of their comments. In the study, in the light of the data of the Banks Association of Turkey, the digital banking data of the 10 most used private banks and 3 state banks and a total of 13 banks constitute the population. The data covers the period from January 2020 to August 2022.In total, between 1,200,000-1,250,000 raw data were obtained from social media platforms where the relevant banks could be interpreted. Banks were examined one by one; Analyzes about word density were applied, wordcloud data visuals were created, and the perspective on banks was measured with individual sentiment analyses. As a result of the study, the most frequently cited by bank customers are The ease, usefulness, and service fees of digital applications are interpreted. Therefore, it has been understood that the digital services of private banks and public banks do not differ much, but the digital services of private banks are more efficient in terms of usefulness and self-renewal. As a result of the analysis, different suggestions were made to banks within the scope of customer satisfaction and quality service delivery in terms of digital banking services.

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• MakaleYalnız künye2024/r/gumushane/19930
  Sağlık Çalışanlarının Ekolojik Ayak İzi Azaltılması Konusundaki Eğilimlerinin İncelenmesi

  Çam, Handan; Menteşe, Fatma Gökçe

  Dünya nüfusunun hızla artması ve teknolojik gelişmeler dünyadaki kaynakların bilinçsizce tüketilmesine neden olmaktadır. Öyle ki insanlar tarafından sonsuz kabul edilen kaynaklar maalesef insani faaliyetler sonucu yapılan tüketim kadar hızlı bir şekilde yenilenememektedir. Bu nedenle ortaya çıkan ekolojik ayak izi kavramı, insanların her türlü faaliyeti sonucunda ekosistemler üzerinde ortaya çıkan izleri ifade eden bir ölçüm yöntemidir. Son yıllarda ekolojik ayak izi kavramı, farkındalığın yaratılması ve ekolojik ayak izi azaltılması önem kazanmıştır. Literatürde ekolojik ayak izi hesaplanması ve farkındalığına dair pek çok çalışma bulunmasına rağmen, ekolojik ayak izinin azaltılmasına yönelik eğilimlerin incelenmesi konusunda sınırlı sayıda çalışma bulunmaktadır. Çalışmanın amacı sağlık sektöründe çalışan bireylerin ekolojik ayak izi konusundaki farkındalıkları ve ekolojik ayak izini azaltmaya yönelik eğilimlerinin değerlendirilmesidir. Bu amaç doğrultusunda Trabzon ilindeki 263 sağlık çalışanına “Ekolojik Ayak İzi Farkındalık Ölçeği” uygulanmıştır. Ekolojik ayak izi alt boyutları; yaş, cinsiyet, medeni durum, kurum içi konum ve eğitim değişkenleri için SPSS 23 paket programı ile analiz edilmiş ve yorumlanmıştır.

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• MakaleAçık Erişim2024/r/gumushane/14534
  Sentiment analysis of financial Twitter posts on Twitter with the machine learning classifiers

  Cam, Handan; Cam, Alper Veli; Demirel, Ugur; Ahmed, Sana

  This paper presents a sentiment analysis combining the lexicon-based and machine learning (ML)-based approaches in Turkish to investigate the public mood for the prediction of stock market behavior in BIST30, Borsa Istanbul. Our main motivation behind this study is to apply sentiment analysis to financial-related tweets in Turkish. We import 17189 tweets posted as "#Borsaistanbul, #Bist, #Bist30, #Bist100″ on Twitter between November 7, 2022, and November 15, 2022, via a MAXQDA 2020, a qualitative data analysis program. For the lexicon-based side, we use a multilingual sentiment offered by the Orange program to label the polarities of the 17189 samples as positive, negative, and neutral labels. Neutral labels are discarded for the machine learning experiments. For the machine learning side, we select 9076 data as positive and negative to implement the classification problem with six different supervised machine learning classifiers conducted in Python 3.6 with the sklearn library. In experiments, 80 % of the selected data is used for the training phase and the rest is used for the testing and validation phase. Results of the experiments show that the Support Vector Machine and Multilayer Perceptron classifier perform better than other classifiers with 0.89 and 0.88 accuracy and AUC values of 0.8729 and 0.8647 respectively. Other classifiers obtain approximately a 78,5 % accuracy rate. It is possible to increase sentiment analysis accuracy with parameter optimization on a larger, cleaner, and more balanced dataset by changing the pre-processing steps. This work can be expanded in the future to develop better sentiment analysis using deep learning approaches.

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• MakaleYalnız künye2022/r/gumushane/17319
  Gümüşhane Üniversitesinin Dijital Dönüşüm ve Covid-19 Pandemisine İlişkin Çalışmalarının Değerlendirilmesi

  Çam, Handan; Çakır, Günay; Zeybek, Halil İbrahim; Sipahi, Ferkan

  Dünya, 2019 yılında ortaya çıkan ve 2020 yılı başında pandemiye dönüşen SARS-CoV virüs salgını ile mücadele etmeye başlamış ve salgın tüm yaşam biçimimizi etkilemiştir. Bu zorlu süreçte tüm insanlık bir arada savaş vermek zorunda kalmıştır. Salgından önce teknolojik gelişmeler ve çevresel kirlilikler hayatımızın her alanında etkili olmaya başlamışken, salgınla eğitimde de radikal değişiklikler olmuştur. Ülkemizde salgın öncesi az sayıda üniversite uzaktan eğitimde ön planda yer almıştır. Yükseköğretim Kurulu, pandemiden önce, üniversitelerde dijital teknoloji kullanımını yaygınlaştırma stratejisi ile geleceği görerek etkili bir adım atmış ve “Yükseköğrenimde Dijital Dönüşüm Projesi” başlatmıştır. Bilgi teknolojileri kullanımının yaygınlaşması, öğrenme tekniklerinin değişmesi, toplumsal istekler, öğrenen/öğreten profili ve son olarak pandemi, dijital dönüşümde etkili olmuştur. Dijital dönüşümün gerekliliği, pandemi döneminde daha belirgin şekilde anlaşılmıştır ve yaşanılan zorluklar, toplumlarda farklı eğilimlerin daha hızlı benimsenmesine neden olmuştur. Gümüşhane Üniversitesi de Yükseköğretim Kurulu’nun 2018 yılında başlattığı Dijital Dönüşüm Projesi’ne ikinci aşamada dahil olmuştur. Bu çalışmanın ana amacı da Gümüşhane Üniversitesinin COVID-19 pandemisi dönemindeki dijital dönüşüm ve pandemi odaklı çalışmaların bir kısmını değerlendirmektir. Sonuç olarak, Gümüşhane Üniversitesinin pandemi süreci boyunca oldukça başarılı faaliyetler yürütmüş ve dijitalleşmeyi eğitimin her alanına yaymak adına önemli çabalar sarf etmiştir.

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• MakaleAçık Erişim2022/r/gumushane/17221
  Analysing user resistance to distance learning systems by academics within the COVID-19 pandemic using the technology acceptance model

  Çam, Handan; Bekar, Fevziye

  The aim of this study is to determine academics’ user resistance to distance learning, their perceptions of the distance learning systems and factors affecting their perceptions of the changes in the education system during the COVID-19 pandemic. The study’s population consists of 440 academics working in 43 different universities in Turkey. The research sample were determined through convenience and snowball sampling methods. The data were collected using an online questionnaire form created within Google Forms. After validity and reliability analyses on the data, eight different hypotheses were tested using structural equation analysis. All eight hypotheses proposed within the study were accepted after receiving the results of this analysis. The results of the study show that user resistance has a significantly negative effect on the users that utilise distance learning. However, the perceived ease of use and usefulness have a significantly positive effect on attitude and behavior.

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