who really invented bitcoin
Unmasking Satoshi Nakamoto: A Stylometric Analysis Aneshia Jordan Course Code Course Title Instructors Name Date i Abstract This research intends to use stylometric analysis that has proven very helpful in the study of the mystery of Bitcoin’s creator, who installed himself as Satoshi Nakamoto. We analyzed the word frequency distributions that would be expected from Satoshi (the supposed pseudonymous inventor of Bitcoin) and then compared these with the ones by the persons who seemed to be the possible contenders of the creator, i.e., Dorian Nakamoto, Hal Finney, and Nick Szabo. This approach might reveal linguistic features that can give us an answer to the long-standing question of the identity of First, by applying the chi-square test to analyze the frequency of the certain keywords, we found that there was no significant difference between the wording used by Dorian (χ2 = 5.5, (p) = 0.0639) and Finney (χ² = 4.0, (p) = 0.1353) compared to Satoshi, which indicated that they had similar This research, as Figure 1 portrays, demonstrate the level of complexity in the ascription of authorship based on the word frequency perspective and advances the notion of the need for a comprehensive approach in place. His possible identification as Satoshi Nakamoto carries ponderous implications for the future of cryptocurrency, underlining the significance of the archeological search of the ancient author’s sanctuary within the more comprehensive context of digital authentication and authorship (Warmke, 2024). It is the duty of future researchers to include many feature sets as of their diverse linguistic indicators and the real massive textual material for them to be able to sharpen the search for Nakamoto’s mysterious identity. Table of Contents Abstract ……………………………………………………………………………………………………………………… i Introduction ……………………………………………………………………………………………………………….. 1 Literature Review……………………………………………………………………………………………………….. 1 Methods…………………………………………………………………………………………………………………….. 2 Results ………………………………………………………………………………………………………………………. 4 Data Presentation ……………………………………………………………………………………………………….. 4 Results ………………………………………………………………………………………………………………………. 5 Interpretation ……………………………………………………………………………………………………………… 6 Comparative Analysis …………………………………………………………………………………………………. 6 Identification of the Candidate……………………………………………………………………………………… 7 Discussion …………………………………………………………………………………………………………………. 7 Conclusion ………………………………………………………………………………………………………………… 8 References …………………………………………………………………………………………………………………. 9 1 Introduction In 2008, Bitcoin, for the first time, totally shook up finance and proclaimed itself the first cryptocurrency in the world. This newly created media, whose foundation does not rely on the central ledger and is secured by encryption, was the forerunner to changes in the way digital transactions can be managed without the need for a central authority. This sign of pseudo-anonymity by the person who works under the alias Satoshi Nakamoto has generated a lot of interest that is yet unanswered. Nowadays, the incognito character persists in entertaining a lot of guesses, not only among but also between technological professionals and even those who do not pertain to this field. Imagining the history of Satoshi Nakamoto is not just a oneday task resolved with curiosity on a global level but also provides the real core values and potential prospects for Bitcoin. The fulfillment of this endeavor reaches even further, interacting with the concepts of security, trust, and true decentralization importance, which cryptocurrency is famous for. Literature Review Cryptocurrency literature, specifically Bitcoin, is being widely covered from the computer science field to the financial sphere despite the multidisciplinary nature of the work. Socio-cultural studies have had a look into the realm as well. The central idea that a study like this one addresses is the fact of how the original seed to sprout Bitcoin impacted the present state of technology and finance (Panda et al., 2023). The high-ranking concept that belongs to the discussion is the elusive character of Satoshi Nakamoto, whose anonymity has practically become an ongoing debate and an inquiry. The digital cash notion does not start with Bitcoin. Stepping back in time, technologists and thinkers similar to the ones mentioned in Brunton’s “Digital Cash: The History of Invention Before Bitcoin” (2020) invented this. Brunton’s work 2 allows us to illustrate well the atmosphere in which Bitcoin was formed, where technology was combined with the bigger quest for alternative ways of life. Conducting research into the cryptocurrency sphere tends to highlight the technological complexity and innovative nature of Bitcoin (the most prominent cryptocurrency). According to Panda et al. (2023), this type of research brings to light highly likely transformative aspects of blockchain and, what is more, of digital currencies like Bitcoin, which pave the way for implementing decentralized and safe financial operations. Social-economic evaluation of Bitcoin, among others, allows us to acquire insight on specific topics. For example, Rahardja et al. 2021 provide a complicated literature review that describes Bitcoin multi-dimensionally, consisting of both the innovation potential of the asset while also the danger of the excessive possibility that the crypto can be misused for illegal purposes, such as being part of the black marker. Of course, whenever there is a talk about Bitcoin, the topic of Nakamoto’s true identity is brought up. Warmke (2024) deals with this by addressing the challenges of anonymity during the adoption of Bitcoin and the philosophical arguments in terms of trust and authority in digital currencies. From the point of the methodological approaches, stylometry application for author identification becomes most relevant. Works such as those of Ms Deepa et al. (2020) bring forward the importance of using Python for data analysis, a vital tool we are using to assess the attribution of certain writings to Nakamoto and the three other candidates. Methods This inquiry is different from the identification of Satoshi Nakamoto in that it does not have a classic hypothesis as the basis of facts. Unlike the exploratory analysis, the hypothesis I will be able to establish from the data will be a manifestation of the study, sensitive to the inductive approaches portrayed in the recent informatics literature (Mrs Deepa et al., 2020). Manufacturing such a non-committal hypothesis and performance of the stylometric analysis 3 gives the objects to the findings to emerge directly from the stylometric analysis without being distorted by confirmation bias. For data collection, from the Nakamoto Institute website, a collection of writings and code samples from Satoshi Nakamoto was collected, serving as the control sample we will use and compare the pioneers to. Many platforms were used for the comparative surveying of literature by Nick Szabo, Hal Finney, Dorian Nakamoto, and other stalwarts. These platforms include Reddit and the individually run websites that have been used as sources of their published material (Brunton, 2020). They offer an extensive sample for linguistic understanding. Author: Carolin Latteier The basis of our analysis is equal to the stylometric approaches, which are executed using Python for text processing and statistical analysis as the reference is established by (Deepa et al., 2020). The stylometric application used word frequency distributions as a basis because there are previous studies that showed that this method is reliable in identifying the original writer (Panda et al., 2023). We will compare these formations in order to find amid those special linguistic features that could have evidence to be authored by the same writer. In the analysis chi-square test was used to find out the probability, given that the writings of the candidates have the identical writing style as the one of Satoshi Nakamoto, that the incidental occurrence of the word frequencies we observe could seem natural. The analysis of the text focused on substantive content words that occur more frequently than the others, like “and” and “the”; function words were excluded. This decision is based on the explicit procedures of stylometry for the accuracy of writing, which should focus on the author-specific vocabulary (Warmke, 2024). The statistical processing will present a clearer view of each candidate’s stylistic proximity to Satoshi’s writings, thereby providing evidence upon which to base conclusions about the likely authorship of Bitcoin’s white paper. 4 Results Data Presentation For this study, a chi-square test was chosen to analyze the word frequency distribution of the writing whose creator is claimed to be Satoshi Nakamoto; however, we also compared this signature to those of three potential inventors: Dorian Nakamoto, Hal Finney, and Nick Szabo. The figure below shows the actual data representation of this analysis in Fig. 1, whereby the frequency hierarchy of words is drawn. These consequentialting terms, for example, “crypto,” “blockchain,” “smarts,” “bitcoins,” and “contract” – are fundamental to the discourse on Bitcoin development and the open-source technology that supports it. The graph shows that “crypto,” a term that appeared 13 times in Satoshi’s texts, is a significant word in this collection, and it is followed by “Szabo” and “Finney.” Nevertheless, a distinct word “smart” and “contracts” stands out among the words that belong to “Szabo,” implying that he might have had a more diverse range of interests in blockchain 5 Statistical Interpretation: The chi-square test yields Results The choice of the chi-square tests to study the word frequency distribution in the texts of Satoshi Nakamoto, Dorian Nakamoto, Hal Finney, and Nick Szabo was intentional. Visual and quantitative data represented in Figure 1 compares the frequency of the uses of a set of words that describe crypto finance and help understand what Bitcoin stands for. A chi-square statistic value of 5.5 having an associated p-value of 0.0639 for Dorian is that the discrepancy in term count from Satoshi’s initial writing is not significant at the traditional 0.05 alpha level (Brunton, 2020). Exploring the data from Finney’s works, one gets 6 a chi-square statistic of 4 and a p-value of 0.1353, which fails to fulfill the statistical significance standard (Panda et al., 2023). Such p-values imply that though there can be two distinctive utilization of some words, there is not enough of them or no significant difference between the frequency of the words used by our candidates and those words that were used by Satoshi (Rahardja et al., 2021). Interpretation Comparative Analysis The chi-square analysis can be seen in this case as a tool that highlights the coincidence rate when the frequency tables of Satoshi Nakamoto and the candidates were compared. For this purpose, statistical scores calculate the probability of the writer being involved in the creation of the texts based on similar features like single words occurring more often than others. In the course of our investigation, the chi-square values for both Dorian and Finney showed an increase in mesure and thus did not have a statistically significant difference from Satosi’s writing. The chi-square test statistics of 5.5 (p = 0.0639) for Dorian and 4.0 (p = 0.1353) for Finney indicate that there is no noticeably different language used during their campaigns compared to the linguistic patterns recognized in Satoshi’s texts inaccurate reference to Brunton, 2020 and Panda et al. The findings are contextualization should be done carefully though with a pinch of background in stylometric analysis. Stylometry is based on the idea that, in every writer, the fingerprint of language is rudimentary but specific enough to the author for that writer to be recognized by his or her style. The present study is concerned with analyzing the word order only, but it can be extended to include the syntactic patterns, lexical selections, and habits for semantics (2024 Warmke). The evidence of the word frequencies is not suggestive of author attribution. This is because these units may be found in different texts written by different authors; hence, the phenomenon is always just a resemblance clue to guide further investigations. 7 Identification of the Candidate Through chi-squared tests, we see that Dorian is more likely Satoshi than Finney because of the slightly lower p-value. This means that Darian’s writings show the closest level of harmony with Satoshi’s known writing style. These scores, however, offer no in-depth conclusive evidence of individual identification despite being precise. Being the fact that Szabo’s chi-square score has not been reported; therefore, so it is infeasible to him on this direct comparison. Despite this, what Szabo articulated shows that he is keen on a somewhat specific purpose and, so, can be harder to contrast to what is known by Satoshi in terms of stylistic expression (Rahardja et al., 2021). It is crucial to note that the outcomes we get from the statistic analysis are only tentative assumption since the analysis itself has some constrains. The lack of a statistically significant difference, however, does not rule out the chances of a correct identification of an individual. This kind of data merely provides the investigators with the exclusion of other cases. As discussed by Mrs. Deepa and Posse (2020), the use of machine learning algorithms and a larger vocabulary of stylometric functions could increase the precision rate in authorship attention. Also, a limited number of entities and the only coverage of specific keywords diminish enough the analysis. Enlarging the common and variety of language markers envisaged can ascertain clearer findings (Panda et al., 2023). Discussion To date already, the investigative soil of Satoshi Nakamoto is still driving public curiosity and academic research. These findings of this research paper – Dorian and Finney’s words come out to be similar but not identical to that of Satoshi Nakamoto’s, as suggested by a section which believes both of them to have the same possibility of being Satoshi himself/herself (Brunton, 2020). These findings thus corroborate certain earlier suspicions, 8 which have largely hinged on the fact that Nakamoto evinces the same tendencies as the unknown individuals that were previously mentioned. Nonetheless, the reports do not rise the network to the account of that of an expert acceptance but instead tell the audience that further information is needed. In order to enhance the quality of the presented research, further projects must encompass a richness of stylometric features, e.g., syntax patterns, idiolectal traits, and semantical objects (Rahardja et ai, 2021). Machine learning techniques might also be used to obtain more accurate analyses of authorship, thus presenting a higher predictive power for the determination of Satoshi Nakamoto. Besides that, it can be possible to grow the corpus by including more texts that are sourced from the candidates will help make the understanding of candidates` writing styles more thorough. A longitudinal study tracing word changes during different periods might also corroborate the extrapolation of candidates’ creativity side by side with other readers’ writing styles (Mrs Deepa et al., 2020). Conclusion The attempt to determine the creator of Bitcoin through the numerical analysis of words could have been more successful as the technique did not identify Satoshi Nakamoto for the role. The mystery of the uncertain authorship embedded in the study of Dorian Nakamoto and Hal Finney stands behind the language test. No elements of authenticity have been revealed yet. In this respect, only linguistic similarities have been found (Brunton, 2020; Panda et al., 2023). Consequently, the results fit into the Bitcoin governance system and its issues with related legal matters from its past. Future studies should improve the methodology of stylometry and the algorithms involved to focus on the wide range of questions about Nakamoto while being a key figure in the history of science and technology (Warmke, 2024; Mrs. Deepa et al., 2020; Rahardja et al., 2021). 9 References Brunton, F. (2020). Digital cash: The unknown history of the anarchists, utopians, and technologists who created cryptocurrency. Princeton University Press. Mrs Deepa, R., Ravikumar, G. K., Ms Kavitha, H. M., & Mrs Divya, B. M. (2020). PYTHON for data analysis. IJRAR-International Journal of Research and Analytical Reviews (IJRAR), 7(1), 740-743. Panda, S. K., Sathya, A. R., & Das, S. (2023). Bitcoin: Beginning of the cryptocurrency era. In Recent Advances in Blockchain Technology: Real-World Applications (pp. 25-58). Cham: Springer International Publishing. Rahardja, U., Aini, Q., Harahap, E. P., & Raihan, R. (2021). Good, bad and dark bitcoin: A systematic literature review. Aptisi Transactions on Technopreneurship (ATT), 3(2), 115-119. Warmke, C. (2024). What is bitcoin. Inquiry, 67(1), 25-67.
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