Not All Influence is Born Equal: On the Effects of Various Types of Behavioral Influence Relationships on Social Media

Typically, online social influence is analyzed using a single metric approach. However, social influence is not monolithic; different users exercise different influences in different ways, and influence is correlated with the user and content-specific attributes. One such attribute could be whether the action is an initiation of a new post, a contribution to a post, or a sharing of an existing post. Thus, this dissertation uses this platform-independent action classification and models the influence as multiple entities and examines social networks through the perspective of behavioral influence propagation. Two empirical studies are present in this dissertation. The first study presents a novel method for tracking these influence relationships over time, which we call influence cascades, and presents a visualization technique to understand these cascades better. These influence patterns are investigated within and across online social media platforms using empirical data and comparing to a scale-free network as a null model. Our results show that characteristics of influence cascades and patterns of influence are, in fact, affected by the platform and the community of the users. The second study applies the same framework to re-construct interconnected social networks and explores the significance of cross-platform influence on social media users in the influence process. In particular, we explore the social dynamics of users with a higher number of social influence relationships across platforms, which we call interface users, and those with fewer social influence relationships across platforms, which we call core users. Our results find that interface users are more vulnerable to being influenced and influential than core users. Further, our results show that the interface users who are influenced to do initiation action exert significantly more influence on others than those who are influenced to contribute

THE INFLUENCERS: FACEBOOK’S LIBRA, PUBLIC BLOCKCHAINS, AND THE ETHICAL CONSIDERATIONS OF CENTRALIZATION

The theoretical promise of blockchain technology is truly extraordinary: a peer-to-peer distributed immutable ledger that could revolutionize economies, societies, and even our daily lives. But what if blockchain technology is not as decentralized as people think? What are the ramifications if, in reality, a blockchain’s core decisions are actually influenced by small groups of people or corporations? This short article seeks to answer that question, by demonstrating that decentralized public blockchains are only as immutable as the decentralization of their governance. Moreover, the announcement of Libra, Facebook’s new permissioned blockchain, shows a growing trend of centralized control around decentralized technologies. Libra is intended to run on highly distributed technology, but will be governed by, and therefore could be arguably controlled by, a highly centralized group of billion-dollar corporations. Accordingly, this article exposes the ways in which blockchain centralization is leaving important decisions to small groups of people or corporations. These blockchain “agents of influence” have more power than many blockchain proponents acknowledge. Whenever human decision-making processes are in effect, the possibility of bias, conflicts of interest, and other ethical concerns will arise. Ironically, it is exactly this type of flawed human process that the blockchain was designed to solve. This article therefore argues that as states design laws to regulate blockchain technology, they should consider adding ethical obligations to combat the problems inherent whenever small groups of people make influential decisions. By adopting ethical guidelines at this early stage, while the technology is still evolving, states and blockchain enthusiasts may abate public fears of blockchain technology and prevent larger ethical crises from developing down the road

The Influencers: Facebook\u27s Libra, Public Blockchains, And the Ethical Considerations of Centralization

The theoretical promise of blockchain technology is truly extraordinary: a peer-to-peer distributed immutable ledger that could revolutionize economies, societies, and even our daily lives. But what if blockchain technology is not as decentralized as people think? What are the ramifications if, in reality, a blockchain’s core decisions are actually influenced by small groups of people or corporations? This short article seeks to answer that question, by demonstrating that decentralized public blockchains are only as immutable as the decentralization of their governance. Moreover, the announcement of Libra, Facebook’s new permissioned blockchain, shows a growing trend of centralized control around decentralized technologies. Libra is intended to run on highly distributed technology, but will be governed by, and therefore could be arguably controlled by, a highly centralized group of billion-dollar corporations. Accordingly, this article exposes the ways in which blockchain centralization is leaving important decisions to small groups of people or corporations. These blockchain “agents of influence” have more power than many blockchain proponents acknowledge. Whenever human decision-making processes are in effect, the possibility of bias, conflicts of interest, and other ethical concerns will arise. Ironically, it is exactly this type of flawed human process that the blockchain was designed to solve. This article therefore argues that as states design laws to regulate blockchain technology, they should consider adding ethical obligations to combat the problems inherent whenever small groups of people make influential decisions. By adopting ethical guidelines at this early stage, while the technology is still evolving, states and blockchain enthusiasts may abate public fears of blockchain technology and prevent larger ethical crises from developing down the road

QAnon Propaganda on Twitter as Information Warfare: Influencers, Networks, and Narratives

QAnon refers to a set of far-right, conspiratorial ideologies that have risen in popularity in the U.S. since their initial promotion in 2017 on the 4chan internet message board. A central narrative element of QAnon is that a powerful group of elite, liberal members of the Democratic Party engage in morally reprehensible practices, but that former U.S. President Donald J. Trump was prosecuting them. Five studies investigated the influence and network connectivity of accounts promoting QAnon on Twitter from August, 2020 through January, 2021. Selection of Twitter accounts emphasized on-line influencers and "persons of interest" known or suspected of participation in QAnon propaganda promotion activities. Evidence of large-scale coordination among accounts promoting QAnon was observed, demonstrating rigorous, quantitative evidence of "astroturfing" in QAnon propaganda promotion on Twitter, as opposed to strictly "grassroots" activities of citizens acting independently. Further, evidence was obtained supporting that networks of extreme far-right adherents engaged in organized QAnon propaganda promotion, as revealed by network overlap among accounts promoting far-right extremist (e.g., anti-Semitic) content and insurrectionist themes; New Age, occult, and "esoteric" themes; and internet puzzle games like Cicada 3301 and other "alternate reality games." Based on well-grounded theories and findings from the social sciences, it is argued that QAnon propaganda on Twitter in the months circa the 2020 U.S. Presidential election likely reflected joint participation of multiple actors, including nation-states like Russia, in innovative misuse of social media toward undermining democratic processes by promoting "magical" thinking, ostracism of Democrats and liberals, and salience of White extinction narratives common among otherwise ideologically diverse groups on the extreme far-right.Comment: 60 pages, 14 figure

Blockchain Regulations and Decentralized Applications: Panel Report from AMCIS 2018

Blockchain represents one of the 21st century’s most impactful inventions. In addition to creating cryptocurrencies such as Bitcoin, this technology enables smart contract functionality and supports decentralized, secure, and private transactions. By design, blockchains enable decentralized functionality for many of today’s business applications and transform traditional centralized information systems. In this paper, we summarize four research areas that will appeal to IS scholars that a panel at AMCIS 2018 discussed: 1) cryptocurrency regulation, 2) Etherisc (a smart contract-based application), 3) decentralized blockchain applications in healthcare, and 4) Bitcoin as a blockchain application and issues with decentralization. To account for the European Union’s General Data Protection Regulation’s requirements to provide people with the right to be forgotten and modify personal data, we modified Pedersen et al.’s (2019) framework to accommodate off-chain data storage requirements. We deployed Pedersen et al.’s (2019) modified framework to evaluate whether one can use blockchains for three different applications. We summarize several research questions and present a research agenda that emerged from the issues highlighted during the panel discussion

Blocks\u27 Network: Redesign Architecture based on Blockchain Technology

The Internet is a global network that uses communication protocols. It is considered the most important system reached by humanity, which no one can abandon. However, this technology has become a weapon that threatens the privacy of users, especially in the client-server model, where data is stored and managed privately. Additionally, users have no power over their data that store in a private server, which means users’ data may interrupt by government or might be sold via service provider for-profit purposes. Furthermore, blockchain is a technology that we can rely on to solve issues related to client-server model if appropriately used. However, blockchain technology uses consensus protocol, which is used for creating an incontrovertible system of agreement between members across a distributed network. Thus, the consensus protocol is used to slow all member down from generating too fast in order to control the network creation pattern, which leads to scalability and latency problems. The proposed system will present a platform that leverages modernize blockchain called Blocks’ Network. The system is taking into consideration the issues related to privacy and confidentiality from the client-side model, and scalability and latency issues from the blockchain technology side. Blocks’ network is a public and a permissioned network that use a multi-dimensional hash to generate multiple chains for the purpose of a systematic approach. The proposed platform is an assembly point for users to create a decentralized network using P2P protocols. The system has high data flow due to frequent use by participants (for example, the use of the Internet). Besides, the system will store all traffic of the network overtly via Blocks’ Network

Development of a cryptocurrency bot

As an emerging market and research direction, cryptocurrencies and cryptocurrency trading have seen considerable progress and a notable upturn in interest and activity, even entering the market people without experience or sufficient knowledge. In addition, the tremendous volatility and the fact that this market never closes make the human factor affect crypto asset trading too much. Hence, in this project a cryptocurrency trading bot is developed. To be exact, the algorithm consists of two distinguishable parts: the bot itself and the backtesting. Notwithstanding that both parts departs from the analysis of financial markets in general, and cryptocurrencies in particular, both present clear differences in terms of code and pretext. On the one hand, the bot’s algorithm is used to trade in reality, specifically through the Binance exchange. Here the user plays risks their monetary capital. On the other hand, backtesting consists of verifying the trading strategy based on historical data. Backtesting serves, then, as validation of the strategy to be followed by the bot. Thus, all the necessary fundamentals to understand both the general cryptocurrency context and technical analysis relevant concepts are presented, along with a detailed explanation of the implemented algorithm and a proper analysis of the obtained results. Finally, further code improvements and new ideas to develop in the future are suggested, apart from presenting the code developed

Predicting the price of Bitcoin using the sentiment of popular Bitcoin-related Tweets

In little over a decade, cryptocurrencies have become a highly speculative asset class in global financial markets, with Bitcoin leading the way. Throughout its relatively brief history, the price of bitcoin has gone through multiple cycles of growth and decline. As a consequence, Bitcoin has become a widely discussed – and polarizing – topic on Twitter. This work studies whether the sentiment of popular Bitcoin-related tweets can be used to predict the future price movements of bitcoin. In total, seven different algorithms are evaluated: Vector Autoregression, Vector Autoregression Moving-Average, Random Forest, XGBoost, LightGBM, Long Short-Term Memory, and Gated Recurrent Unit. By applying lexicon-based sentiment analysis, and heuristic filtering of tweets, it was discovered that sentiment-based features of popular tweets improve the prediction accuracy over baseline features (open-high-low-close data) in five of the seven algorithms tested. The tree-based algorithms (Random Forest, XGBoost, LightGBM) generally had the lowest prediction errors, while the neural network algorithms (Light Short-Term Memory and Gated Recurrent Unit) had the poorest performance. The findings suggest that the sentiment of popular Bitcoin-related tweets can be an important feature in predicting the future price movements of bitcoin

Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies

This research analyses high-frequency data of the cryptocurrency market in regards to intraday trading patterns related to algorithmic trading and its impact on the European cryptocurrency market. We study trading quantitatives such as returns, traded volumes, volatility periodicity, and provide summary statistics of return correlations to CRIX (CRyptocurrency IndeX), as well as respective overall high-frequency based market statistics with respect to temporal aspects. Our results provide mandatory insight into a market, where the grand scale employment of automated trading algorithms and the extremely rapid execution of trades might seem to be a standard based on media reports. Our findings on intraday momentum of trading patterns lead to a new quantitative view on approaching the predictability of economic value in this new digital market