Examining Heterogeneity Structured on a Large Data Volume with Minimal Incompleteness

Aljojo, Nahla (2021) Examining Heterogeneity Structured on a Large Data Volume with Minimal Incompleteness. ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY, 9 (2). pp. 30-37. ISSN 2410-9355

Text (Research Artical) ARO.10857-Vol9.No2.2021.ISSUE16-PP 30-37.pdf - Published Version Available under License Creative Commons Attribution Non-commercial Share Alike. Download (1MB)

Abstract

While Big Data analytics can provide a variety of benefits, processing heterogeneous data comes with its own set of limitations. A transaction pattern must be studied independently while working with Bitcoin data, this study examines twitter data related to Bitcoin and investigate communications pattern on bitcoin transactional tweet. Using the hashtags #Bitcoin or #BTC on Twitter, a vast amount of data was gathered, which was mined to uncover a pattern that everyone either (speculators, teaches, or the stakeholders) uses on Twitter to discuss Bitcoin transactions. This aim is to determine the direction of Bitcoin transaction tweets based on historical data. As a result, this research proposes using Big Data analytics to track Bitcoin transaction communications in tweets in order to discover a pattern. Hadoop platform MapReduce was used. The finding indicate that In the map step of the procedure, Hadoop's tokenize the dataset and parse them to the mapper where thirteen patterns were established and reduced to three patterns using the attributes previously stored data in the Hadoop context, one of which is the Emoji data that was left out in previous research discussions, but the text is only one piece of the puzzle on bitcoin transaction interaction, and the key part of it is “No certainty, only possibilities” in Bitcoin transactions

Item Type:	Article
Uncontrolled Keywords:	Heterogenouis dataset, Bitcoin transactions, Bitcoin tweets
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	ARO-The Scientific Journal of Koya University > VOL 9, NO 2 (2021)
Depositing User:	Dr Salah Ismaeel Yahya
Date Deposited:	29 Mar 2022 06:26
Last Modified:	29 Mar 2022 06:26
URI:	http://eprints.koyauniversity.org/id/eprint/287

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