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  • 1.
    Farhoudinia, Bahareh
    et al.
    Sabanci University.
    Ozturkcan, Selcen
    Linnaeus University, School of Business and Economics, Department of Marketing and Tourism Studies (MTS).
    Kasap, Nihat
    Emotions unveiled: detecting COVID-19 fake news on social media2024In: Humanities and Social Sciences Communications, E-ISSN 2662-9992, Vol. 11, no 1, article id 640Article in journal (Refereed)
    Abstract [en]

    The COVID-19 pandemic has highlighted the pernicious effects of fake news, underscoring the critical need for researchers and practitioners to detect and mitigate its spread. In this paper, we examined the importance of detecting fake news and incorporated sentiment and emotional features to detect this type of news. Specifically, we compared the sentiments and emotions associated with fake and real news using a COVID-19 Twitter dataset with labeled categories. By utilizing different sentiment and emotion lexicons, we extracted sentiments categorized as positive, negative, and neutral and eight basic emotions, anticipation, anger, joy, sadness, surprise, fear, trust, and disgust. Our analysis revealed that fake news tends to elicit more negative emotions than real news. Therefore, we propose that negative emotions could serve as vital features in developing fake news detection models. To test this hypothesis, we compared the performance metrics of three machine learning models: random forest, support vector machine (SVM), and Naïve Bayes. We evaluated the models’ effectiveness with and without emotional features. Our results demonstrated that integrating emotional features into these models substantially improved the detection performance, resulting in a more robust and reliable ability to detect fake news on social media. In this paper, we propose the use of novel features and methods that enhance the field of fake news detection. Our findings underscore the crucial role of emotions in detecting fake news and provide valuable insights into how machine-learning models can be trained to recognize these features.

  • 2.
    Farhoudinia, Bahareh
    et al.
    Sabanci University, Turkey.
    Ozturkcan, Selcen
    Linnaeus University, School of Business and Economics, Department of Marketing and Tourism Studies (MTS). Sabanci University, Turkey.
    Kasap, Nihat
    Sabanci University, Turkey.
    Fake news in business and management literature: A systematic review of definitions, theories, methods, and implications2023In: Aslib Journal of Information Management, ISSN 2050-3806, E-ISSN 2050-3814Article in journal (Refereed)
    Abstract [en]

    This paper aims to conduct an interdisciplinary systematic literature review of fake news research and to advance the socio-technical understanding of digital information practices and platforms in business and management studies. The paper applies a focused, systematic literature review method to analyze articles on fake news in business and management journals from 2010 to 2020. The paper analyzes the definition, theoretical frameworks, methods, and research gaps of fake news in the business and management domains. It also identifies some promising research opportunities for future scholars. The paper offers practical implications for various stakeholders who are affected by or involved in fake news dissemination, such as brands, consumers, and policymakers. It provides recommendations to cope with the challenges and risks of fake news. The paper discusses the social consequences and future threats of fake news, especially in relation to social networking and social media. It calls for more awareness and responsibility from online communities to prevent and combat fake news. The paper contributes to the literature on information management by showing the importance and consequences of fake news sharing for societies. It is among the frontier systematic reviews in the field that cover studies from different disciplines and focus on business and management studies.

  • 3.
    Farhoudinia, Bahareh
    et al.
    Sabanci University, Turkey.
    Ozturkcan, Selcen
    Linnaeus University, School of Business and Economics, Department of Marketing.
    Kasap, Nihat
    Sabanci University, Turkey.
    Lexicon-based sentiment analysis of fake news on social media2022In: Presented at the AIRSI2022 Conference: Technologies 4.0 in Tourism, Services & Marketing, Zaragoza, Spain, July 11-13, 2022, Zaragoza, Spain, 2022, Zaragoza, Spain, 2022Conference paper (Refereed)
    Abstract [en]

    Social media is considered one of the primary sources of information. Besides all benefits that social media bring to human life, the popularity of social media simultaneously caused a rapid spread of fake news. Fake news poses a serious threat to societies since it enhances the polarity among different ideas, such as political parties. The fake news issue was further exacerbated during the COVID-19 Pandemic, and fake news studies attracted the attention of plenty of researchers (e.g., Apuke & Omar, 2021; Elías & Catalan-Matamoros, 2020). For example, Fake news claiming that 5G cell towers affect the human immune system has led to the burning of some cell towers in Europe (Mourad et al., 2020). Researchers claimed that fake stories spread more rapidly than true ones on social media (Vosoughi et al., 2018). The rapid spread of fake news makes companies and organizations vulnerable. Fake news about a company can directly affect the company's stock price and cause financial losses. A literature review reveals that scholars from multidisciplinary areas are interested in this topic; for instance, psychology scholars aim to answer research questions such as why people believe and share fake news (Talwar et al., 2019) and what are the characteristics of people who share or are involved in the spread of fake news (Ben-Gal et al., 2019; Brashier & Schacter, 2020). Computer science scholars aim to find ways to detect fake news, using machine learning techniques to create detection models (Faustini & Covões, 2020; Ozbay & Alatas, 2020). Emotion and sentiment analysis of fake news have not been studied in the literature; thus, this research will contribute to the field significantly.

  • 4.
    Ozturkcan, Selcen
    et al.
    Linnaeus University, School of Business and Economics, Department of Marketing and Tourism Studies (MTS).
    Kasap, Nihat
    Sabancı University, Turkey.
    Arın, İnanç
    Sabancı University, Turkey.
    Saygın, Yücel
    Sabancı University, Turkey.
    Reflections of Social Support on Twitter: The Case of the Soma Mine Disaster in Turkey2023In: Digitalisation: Opportunities and Challenges for Business. ICBT 2022 / [ed] Alareeni, B., Hamdan, A., Khamis, R., Khoury, R.E., Cham: Springer, 2023, Vol. 621, p. 79-88Conference paper (Refereed)
    Abstract [en]

    Tweets posted during the Soma mine disaster that took place in Turkey provide a better understanding of the potential that social networks have for social support. The social media analytics framework and the text categorization methodology using CovNets were used to analyze 6.3 million tweets containing the keyword “soma” posted between 13 May 2014 and 23 March 2015 in Turkish. According to the findings, people used Twitter more after hearing about the terrible and tragic event. In reaction to the demand for a public day of mourning, Twitter was used to express grief and outrage. Twitter usage has expanded in unison with the involvement of charity and assistance organizations. Regardless, none of the support efforts posted on Twitter garnered widespread public participation. The results, on the other hand, showed that deep learning could accurately predict if a tweet would garner a substantial number of retweets. The findings could be beneficial for people interested in how social support organizations and policymakers use Twitter to keep the public informed during significant disasters.

  • 5.
    Ozturkcan, Selcen
    et al.
    Linnaeus University, School of Business and Economics, Department of Marketing.
    Kasap, Nihat
    Sabanci University, Turkey.
    Ozdinc, Mesut
    Åbo Akademi University, Finland.
    Tanaltay, Altug
    Sabanci University, Turkey.
    Digital national currency: example of Sweden and e-Krona2019In: Paper presented at the 2nd International Conference on Digital Innovation, Entrepreneurship and Financing, Valencia, Spain, December 2-3, 2019, Valencia, Spain, 2019, p. 1-7Conference paper (Refereed)
    Abstract [en]

    Financial Institutions all around the world are recently discussing possibilities to launch national digital currencies to replace the cash as we know it since the Lydians invention. In this paper, we review the concept by visiting the core definitions and focus on the Scandinavian market to understand the example of Sweden and the ongoing e-Krona project. We conclude by pointing out some research questions and call upon developing future collaborative research.

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  • 6.
    Ozturkcan, Selcen
    et al.
    Linnaeus University, School of Business and Economics, Department of Marketing.
    Kasap, Nihat
    Sabanci University, Turkey.
    Tanaltay, Altug
    Sabanci University, Turkey.
    Özdinc, Mesut
    Mimar Sinan FA University, Turkey.
    Analysis of tweets about football: 2013 and 2018 leagues in Turkey2019In: Behavior and Information Technology, ISSN 0144-929X, E-ISSN 1362-3001, Vol. 38, no 9, p. 887-899Article in journal (Refereed)
    Abstract [en]

    Football has recently developed into a unique sector with complex management and marketing functions, where novel communication technologies are employed. In this paper, we aim to contribute to the numerous fields involving emerging European sports marketing literature, social media analytics, and digital consumer behaviour. Our purpose is to explore Twitter use related with football by analysing real-time streamed data in offering a longitudinal perspective by focusing on 2013 and 2018 leagues in Turkey via the use of social media analytics framework. Retrieved dataset involved randomly selected publicly available 370 thousand and 6.8 million real-time tweets in 2013 and 2018 leagues, respectively. We report that majority of tweets about the football was posted within the three-hour window before the match independent of the match result and the importance of the result. Moreover, pre-match tweeting volume was almost a crystal ball signalling match winning. Our findings are valuable for sports managers and marketers where some key suggestions provided are to involve particular contexts of winning or losing in their after-match marketing plans, to value weekdays as much as the weekends, and to utilise the after-work prime time of social media engagement.

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    fulltext
  • 7.
    Tanaltay, Altuğ
    et al.
    Sabanci University, Turkey.
    Ozturkcan, Selcen
    Linnaeus University, School of Business and Economics, Department of Marketing.
    Kasap, Nihat
    Sabanci University, Turkey.
    A Cross-Cultural Analysis of Emoticon Utilization in Social Media Branding Communication2022In: Presented at the AIRSI2022 Conference: Technologies 4.0 in Tourism, Services & Marketing, Zaragoza, Spain, July 11-13, 2022, Zaragoza, Spain, 2022, Zaragoza, Spain, 2022Conference paper (Refereed)
    Abstract [en]

    Despite their omnipresence, certain questions arise about emoticons’ usage in different contexts and languages. There is already a growing literature on cultural differences of preference of emoticons in text communication, however, they are mostly based on artificial experimental designs, thus, their generalizability is limited. Moreover, there still exists a gap in research to concentrate on how people use emoticons, rather than interpret them. especially in branding communication context. This study aims to quantitatively identify cross-cultural differences in English speaking and Turkish speaking Twitter users’ use of emoticons as nonverbal cues regarding Brand Communication context, by getting use of big data analysis seeking answers to the following research questions: (1) (RQ-1) How different is the attitude towards using an emoticon in messages across cultures/languages? (2) (RQ-2) How different are the set of popular emoticons preferred across cultures/languages? • (RQ-2a) Does one culture use a more diverse set of emoticons? • (RQ-2b) How much different are the set of popular emoticons across cultures/languages? (3) (RQ-3) How different emoticons are preferred semantically by certain emotions? We contribute to marketing communication and social media marketing, and aim to reveal alternative analysis methodologies regarding the potential of big data. Our findings are also valuable for understanding the major differences of preference of consumers between local and global markets.

  • 8.
    Tanaltay, Altuğ
    et al.
    Sabanci University, Turkey.
    Ozturkcan, Selcen
    Linnaeus University, School of Business and Economics, Department of Marketing.
    Kasap, Nihat
    Sabanci University, Turkey.
    Unpacking Emotion on Social Media Marketing in Global and Emerging Local Market Contexts with Evidence from Big Data2022In: Presented at the AIRSI2022 Conference: Technologies 4.0 in Tourism, Services & Marketing, Zaragoza, Spain, July 11-13, 2022, Zaragoza, Spain, 2022Conference paper (Refereed)
    Abstract [en]

    Global brands' localization efforts are often reflected in their social media marketing practices with varying acculturation degrees on the tone, emotion, and symbols used. The similarities and differences of parent brands and their local versions' uses of emotional content present an emerging field of research that can uncover the applicable lessons for better business. This research employs supervised and unsupervised machine learning methodologies to explore the emotional content of international automobile and technology brands' Twitter messages in global and emerging local market contexts. Along the same lines, an analysis of consumers' reflections presents cues on positive word of mouth by understanding the most prominent structural and textual features. We aim to answer two main research questions: (1) What are the apparent emotions in international automobile and technology brands' social media marketing in global and emerging local market contexts; and (2) How does the emotional content of an international brand's Twitter marketing campaign message affect the dispersion and positive word of mouth in social media in global and emerging local market contexts. We contribute to marketing, machine learning, social media marketing, and emotion literatures. Our findings are valuable for internationalizing and born-global firms to engage emotionally with their global and emerging market consumers in their social media marketing.

1 - 8 of 8
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  • en-US
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  • nn-NO
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  • Other locale
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