Public Perception Based Recommendation System for Cryptocurrency

Bibi, Shaista; Hussain, Shahid; Faisal, Muhammad

doi:10.1109/ibcast.2019.8667123

Cited by 5 publications

(6 citation statements)

References 10 publications

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“…Cryptocurrency is a type of digital currency that uses the technique of cryptography and blockchain to secure financial transactions (Sudzina & Pavlicek, [2]). This is one of the novel technology around the globe (Bibi,Hussain,& Faisal,[17]). Unlike fiat currencies, cryptocurrencies are decentralized, as they are not issued or backed by any regulatory body or government.…”

Section: Literature Reviewmentioning

confidence: 99%

A Moderated Mediation Model of Factors Influencing Intention to Adopt Cryptocurrency among University Students

Hasan

Ayub

Ellahi

et al. 2022

Human Behavior and Emerging Technologies

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The goal of this study is to find out what people think about cryptocurrencies and how they feel about it. The study used a questionnaire to assess the factors that influence people’s willingness to accept cryptocurrency. The study used a pretest, posttest quantitative analysis to determine the level of awareness among users in the first phase. In the second step, information regarding the conceptual framework was gathered using a survey approach. For the study, 350 university students were chosen as the sample size. Hypotheses about the significant effects of perceived benefits, perceived risks, perceived value, and structural provisions on behavioral intention to adopt cryptocurrency were accepted, while hypotheses about social effects, moderating effect of self-efficacy and personal innovativeness as well as the mediator attitudes towards using cryptocurrency, were not statistically proven. The tested model and resultant findings have brought many managerial and theoretical implications for enhancing the intention to adopt cryptocurrency.

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Section: Literature Reviewmentioning

confidence: 99%

A Moderated Mediation Model of Factors Influencing Intention to Adopt Cryptocurrency among University Students

Hasan

Ayub

Ellahi

et al. 2022

Human Behavior and Emerging Technologies

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“…In [83], topic modeling was performed using online Bitcoin forum data. In [84], topic modeling was performed using Twitter data and LDA to investigate the concerns and sentiment analyses of international users. However, these studies provided limited insights due to their use of data from single source.…”

Section: Discussionmentioning

confidence: 99%

Unveiling Cryptocurrency Conversations: Insights From Data Mining and Unsupervised Learning Across Multiple Platforms

Jung,

Lee,

Kim

2023

IEEE Access

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The rapid growth of the cryptocurrency market has led to an increasing interest in the subject. Cryptocurrency is now recognized as an asset, and laws and financial regulations have begun to emerge for supporting its practical use. As a result, it has become essential to perform data mining and attain knowledge from text data related to cryptocurrency. Previous studies have focused on analyzing data from a single source such as Twitter. However, there are unique insights to be gained from data acro ss multiple platforms. In the present study, we utilized data mining techniques to extract insights from LexisNexis, Web of Science, and Reddit, representing the media, academia, and general public, respectively. Among unsupervised learning technologies, topic modeling was employed for the analysis. Topic modeling is a methodology that uncovers hidden meanings within the collected data. Among the diverse topic modeling techniques available, bidirectional encoder representations from transformers topic was chosen for the analysis. BERTopic considered to be state-of-the-art in the field of topic modeling. Dynamic topic modeling was employed to track changes in themes over time. Our experimental results reveal a tendency in the news to cover major events related to cryptocurrencies, such as regulatory developments and market t rends. Academic papers, on the other hand, tend to focus on the technology behind cryptocurrencies and related research. Finally, social media conversations center more around information delivery from an investor's psychological perspective, such as market sentiment and investment strategies.

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“…Currently, the following key directions can be highlighted: 1) brand and customer management: SA of blogs, tweets and posts is widely used to analyze the brand image, track customer feedbacks and in development of automatic dialogue systems [30], [27], [13], [8]; 2) politics: there is an immense interest in tracking social media sentiment towards politicians, electoral issues, national and international events [1]; 3) public health: SA is especially applicable for detecting depressions [45], cyber-bulling [10], tracking well-being [37], developing social robots [14]; 4) education: diverse tutoring and evaluation systems benefit from SA identifying correctness of answers, emotional state of the participant or teaching quality [25]. While novel promising application areas, such as cryptocurrencies [5] or programming code reviews [24], keep emerging, the SA application in the BP context remains not studied.…”

Section: Sentiment Analysis Application Areasmentioning

confidence: 99%

“…understanding opinions of people about products, services, events, films, or politicians. Some novel SA applied research appeared in the areas of programming code reviews [24], cryptocurrencies [5], forecasting stock markets [28], or dynamic pricing models [43]. Nonetheless, such domain as business processes (BPs) in the context of SA has not been researched so far.…”

Section: Introductionmentioning

confidence: 99%

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

Rizun

Revina

2019

SSRN Journal

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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 the task text. PAE is interpreted as a business process (BP) key performance indicator predicting urgency, criticality and complexity of the BP task processing. Using qualitative evaluation, the researchers proved the workability of both BS concept and its effective application method to measure PAE. As practical contributions of the research, quantitative support in a form of statistical reports and qualitative support in a form of task prioritization recommendations and time management for a BP worker are suggested.

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Public Perception Based Recommendation System for Cryptocurrency

Cited by 5 publications

References 10 publications

A Moderated Mediation Model of Factors Influencing Intention to Adopt Cryptocurrency among University Students

A Moderated Mediation Model of Factors Influencing Intention to Adopt Cryptocurrency among University Students

Unveiling Cryptocurrency Conversations: Insights From Data Mining and Unsupervised Learning Across Multiple Platforms

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

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