Exploring Potential of NFT Brand: COREMAN

Authors

DOI:

https://doi.org/10.36676/sjmbt.v2.i1.04

Keywords:

Coreman, Young Parrot, CoreDao, Blockchain, Avengers, Glamour

Abstract

COREMAN is a prominent NFT brand that has established its NFT collection on the Young Parrot platform. These NFTs are integrated with the Core DAO blockchain, indicating potential governance or utility functionalities within the Core DAO ecosystem. The collection boasts a diverse range of themes, including Avengers, Stylist Pitbull, Glamour, Happy Birthday, and Exclusive Amulet series. This abstract provides a glimpse into COREMAN's NFT offerings, highlighting their presence on Young Parrot and their association with the Core DAO blockchain.

References

A. Singla and M. Gupta, “9NFTMANIA: BRIDGING NFT ART AND DIGITAL CURRENCY WITH 9NM TOKENS”, SJMBT, vol. 2, no. 1, pp. 1–6, Feb. 2024. DOI: https://doi.org/10.36676/sjmbt.v2.i1.01

M. Gupta, “Love in the Blockchain: Unique NFT Gifts for Lovers”, SJMBT, vol. 2, no. 1, pp. 7–12, Feb. 2024. DOI: https://doi.org/10.36676/sjmbt.v2.i1.02

Singla, A., & Gupta, M. (2024). Shaping the Digital Renaissance: The Impact of Glamorous NFT Collections. Scientific Journal of Metaverse and Blockchain Technologies, 2(1), 13–17. https://doi.org/10.36676/sjmbt.v2.i1.03 DOI: https://doi.org/10.36676/sjmbt.v2.i1.03

M. M. Bailey, “Detecting Propagators of Disinformation on Twitter Using Quantitative Discursive Analysis,” pp. 1–12, 2022, [Online]. Available: http://arxiv.org/abs/2210.05760.

M. S. Akter, H. Shahriar, N. Ahmed, and A. Cuzzocrea, “Deep Learning Approach for Classifying the Aggressive Comments on Social Media: Machine Translated Data Vs Real Life Data,” Proc. - 2022 IEEE Int. Conf. Big Data, Big Data 2022, pp. 5646–5655, 2022, doi 10.1109/BigData55660.2022.10020249. DOI: https://doi.org/10.1109/BigData55660.2022.10020249

B. Wei, J. Li, A. Gupta, H. Umair, A. Vovor, and N. Durzynski, “Offensive Language and Hate Speech Detection with Deep Learning and Transfer Learning,” 2021, [Online]. Available: http://arxiv.org/abs/2108.03305.

A. Wadhawan and A. Aggarwal, “Towards Emotion Recognition in Hindi-English Code-Mixed Data: A Transformer Based Approach,” WASSA 2021 - Work. Comput.Approaches to Subj. Sentim.Soc.Media Anal. Proc. 11th Work., pp. 195–202, 2021.https://aclanthology.org/2021.wassa-1.21.

A. K. Chanda, Efficacy of BERT embeddings on predicting disaster from Twitter data, vol. 1, no. 1. Association for Computing Machinery, 2021.[Online]. Available: http://arxiv.org/abs/2108.10698.

N. A. Azeez, S. O. Idiakose, C. J. Onyema, and C. Van Der Vyver, “Cyberbullying Detection in Social Networks: Artificial Intelligence Approach,” J. Cyber Secure. Mobil., vol. 10, no. 4, pp. 745–774, 2021, doi: 10.13052/jcsm2245-1439.1046. DOI: https://doi.org/10.13052/jcsm2245-1439.1046

D. Antonakaki, P. Fragopoulou, and S. Ioannidis, “A survey of Twitter research: Data model, graph structure, sentiment analysis, and attacks,” Expert Syst. Appl., vol. 164, no. September 2020, p. 114006, 2021, doi: 10.1016/j.eswa.2020.114006. DOI: https://doi.org/10.1016/j.eswa.2020.114006

K. N. Alamet al., “Deep Learning-Based Sentiment Analysis of COVID-19 Vaccination Responses from Twitter Data,” Comput.Math. Methods Med., vol. 2021, 2021, doi: 10.1155/2021/4321131. DOI: https://doi.org/10.1155/2021/4321131

C. Zhang, B. Wilkinson, A. Ganesan, and T. Oates, “Determining the Scale of Impact from Denial-of-Service Attacks in Real Time Using Twitter,” 2019, doi: 10.1145/3306195.3306199.

V. Sivasangari, A. K. Mohan, K. Suthendran, and M. Sethumadhavan, “Isolating rumors using sentiment analysis,” J. Cyber Secure.Mobil., vol. 7, no. 1, pp. 181–200, 2018, doi: 10.13052/jcsm2245-1439.7113. DOI: https://doi.org/10.13052/2245-1439.7113

Gupta, M., Gupta, D., & Duggal, A. (2023). NFT Culture: A New Era. Scientific Journal of Metaverse and Blockchain Technologies, 1(1), 57–62. https://doi.org/10.36676/sjmbt.v1i1.08 DOI: https://doi.org/10.36676/sjmbt.v1i1.08

M. Gupta, “Reviewing the Relationship Between Blockchain and NFT With World Famous NFT Market Places”, SJMBT, vol. 1, no. 1, pp. 1–8, Dec. 2023.

R. Gupta, M. Gupta, and D. Gupta, “Role of Liquidity Pool in Stabilizing Value of Token”, SJMBT, vol. 1, no. 1, pp. 9–17, Dec. 2023. DOI: https://doi.org/10.36676/sjmbt.v1i1.02

M. GUPTA and D. Gupta, “Investigating Role of Blockchain in Making your Greetings Valuable”, URR, vol. 10, no. 4, pp. 69–74, Dec. 2023. DOI: https://doi.org/10.36676/urr.2023-v10i4-009

R. Issalh, A. Gupta, and M. Gupta, “PI NETWORK : A REVOLUTION”, SJMBT, vol. 1, no. 1, pp. 18–27, Dec. 2023. DOI: https://doi.org/10.36676/sjmbt.v1i1.03

A. Duggal, M. Gupta, and D. Gupta, “SIGNIFICANCE OF NFT AVTAARS IN METAVERSE AND THEIR PROMOTION: CASE STUDY”, SJMBT, vol. 1, no. 1, pp. 28–36, Dec. 2023. DOI: https://doi.org/10.36676/sjmbt.v1i1.04

M. Gupta, “Say No to Speculation in Crypto market during NFT trades: Technical and Financial Guidelines”, SJMBT, vol. 1, no. 1, pp. 37–42, Dec. 2023. DOI: https://doi.org/10.36676/sjmbt.v1i1.05

A. Singla, M. Singla, and M. Gupta, “Unpacking the Impact of Bitcoin Halving on the Crypto Market: Benefits and Limitations”, SJMBT, vol. 1, no. 1, pp. 43–50, Dec. 2023. DOI: https://doi.org/10.36676/sjmbt.v1i1.06

Gupta and P. Jain, “EXPECTED IMPACT OF DECENTRALIZATION USING BLOCKCHAIN BASED TECHNOLOGIES”, SJMBT, vol. 1, no. 1, pp. 51–56, Dec. 2023. DOI: https://doi.org/10.36676/sjmbt.v1i1.07

D. Gupta and S. Gupta, “Exploring world famous NFT Scripts: A Global Discovery”, SJMBT, vol. 1, no. 1, pp. 63–71, Dec. 2023. DOI: https://doi.org/10.36676/sjmbt.v1i1.09

M. Gupta, “Integration of IoT and Blockchain for user Authentication”, SJMBT, vol. 1, no. 1, pp. 72–84, Dec. 2023. DOI: https://doi.org/10.36676/sjmbt.v1i1.10

A. Singla and M. Gupta, “Investigating Deep learning models for NFT classification : A Review”, SJMBT, vol. 1, no. 1, pp. 91–98, Dec. 2023. DOI: https://doi.org/10.36676/sjmbt.v1i1.12

Issalh, R., Gupta, D., & Gupta, M. (2023). RESEARCHER ECONOMY: A REVOLUTION BY 9NFTMANIA FOR PRESENT ALPHA MALE. Scientific Journal of Metaverse and Blockchain Technologies, 1(1), 99–104. https://doi.org/10.36676/sjmbt.v1i1.13 DOI: https://doi.org/10.36676/sjmbt.v1i1.13

R. Jangra, “Reviewing the Optimized Mechanism for Deep Learning Based Bot Detection to Evaluate Genuine Crypto Assets”, SJMBT, vol. 1, no. 1, pp. 105–113, Dec. 2023. DOI: https://doi.org/10.36676/sjmbt.v1i1.14

Downloads

Published

2024-02-29

How to Cite

Meenu. (2024). Exploring Potential of NFT Brand: COREMAN. Scientific Journal of Metaverse and Blockchain Technologies, 2(1), 18–24. https://doi.org/10.36676/sjmbt.v2.i1.04
PlumX Metrics

Issue

Section

Original Research Articles

Categories

Similar Articles

1 2 > >> 

You may also start an advanced similarity search for this article.