Kevin K.W. Ho, Dickson K.W. Chiu, C. H. Au, Francis Dalisay · 6 authors
This position article summarizes the panelists’ presentations and discussions at the panel “Fake News, Misinformation, and Privacy: How COVID-19 Pandemic Changed Our Society,” held at the 15th International Conference on Information Resources Management (Conf-IRM 2022) on October 18, 2022. The panel discussed their views on (1) how to stop the spreading of health misinformation; (2) how information sources affect online health information behavior; (3) how news literacy increases people's desire to seek out information by increasing their skepticism; and (4) how political beliefs, trust, and privacy concerns affect people's decisions during COVID-19. This article also discusses how blockchain and distributed ledger technologies can help tackle the fake news and misinformation problem.
Blockchain technology revolutionizes the Internet, but also poses increasing risks, particularly in cryptocurrency finance. On the Ethereum platform, Ponzi schemes, phishing scams, and a variety of other frauds emerge. Existing Ponzi scheme detection approaches based on heterogeneous transaction graph modeling leverages semantic information between node (account) pairs to establish connections, overlooking the semantic attributes inherent to the edges (interactions). To overcome this, we construct heterogeneous Ethereum interaction graphs with multiple triplet interaction patterns to better depict the real Ethereum environment. Based on this, we design a new framework named multi-triplet augmented heterogeneous graph neural network (MAHGNN) for Ponzi scheme detection. We introduce the Conditional Variational Auto Encoder (CVAE) to capture the semantic information of different triplet interaction patterns, which facilitates the characterization on account features. Extensive experiments demonstrate that MAHGNN is capable of addressing the problem of multi-edge interactions in heterogeneous Ethereum interaction graphs and achieving state-of-the-art performance in Ponzi scheme detection.
Geordan Shannon, Alix Faddoul, Alexander Lai, Tony Lai · 7 authors
Planet.Health addresses imagination and coordination challenges for planetary health through innovative approaches to social organising. This report presents the findings from the inaugural Planet.Health event in 2022, including the Planet.Health unconference. An unconference is a participant-driven event format that provides flexibility for emergent ideas and connections. In this (un)conference report, we share the challenges, achievements, and lessons learned during the initial year of activities in the leadup to and following the Planet.Health unconference event. We also discuss how the intersection of web3 and planetary health—a major focus of the first year—provides an alternative lens for envisioning, innovating, and coordinating beyond conventional social and institutional frameworks. We explore the potential impact of web3 technologies and decentralised social, economic, and financial networks and highlight the implications of these approaches for addressing planetary crises and supporting a flourishing human–environment relationship. As a new contribution to the planetary health field, this work emphasises the importance of building decentralised systems to foster creative actions and inspire global engagement for planetary wellbeing. The report concludes with some practical insights on how we begin to build and sustain decentralised social networks, including a discussion of the benefits and limitations of these approaches.
Wenrui Zuo, Aravindh Raman, Raúl J. Mondragón, Gareth Tyson
Web3 social media strives to eliminate the need for centralized management by building upon on technologies such public ledgers and smart contracts. This has generated significant hype, but creates many notable challenges, many of which remain unaddressed. One such challenge is content moderation. Specifically, the immutable nature of blockchain means that it becomes impossible to retrospectively delete posts. This means that illegal content posts cannot be moderated or removed. In an attempt to overcome this, Web3 platforms, such as memo.cash, allow users to filter out posts from their personal timelines. Taking memo.cash as a use case, the goal of this work is to study the efficacy of the approach, and identify associated challenges. A particularly unique feature of memo.cash is that users must pay money (satoshi) for each social action (e.g., posting and blocking other users). We conjecture that this may impact the nature of moderation, particularly among poorer users. To explore this, we gather data from memo.cash covering 24K users, 317K posts, and 2.57M user actions. We investigate how the need to pay may impact the moderation system and propose potential solutions to address the challenges that arise.
Despite its relatively brief history, cryptocurrency has already had a profound impact on the economy, with some predicting that it will eventually replace traditional fiat currencies. Historically, it had dark associations with illegal activities in the early days, although perceptions and associations likely have, in recent years, changed for the better. Thus, understanding how people perceive the morality of cryptocurrency currently forms the motivation of the current research. We, in particular, examine associations dependent on political ideology. Across both a large-scale analysis of Twitter posts ( N = 959,393) and controlled survey research ( N = 487), we find that cryptocurrency is currently best understood as being more strongly linked to conservative vs. liberal moral foundations. Cryptocurrency-related posts were more likely to express conservative moral foundations (Authority, Purity, and Loyalty) rather than liberal moral foundations (Fairness and Care), and individual endorsement of these conservative moral foundations was associated with increased interest in crypto investment.
Today, more than 4 billion people use social media globally now, and this trend is growing year over year with significant implications for privacy. Verification and authentication are highly difficult tasks because of extensive usage of social media-based global news. Several researches have introduced the use of Distributed ledger technology (Blockchain) in social media to address these limitations. The most well-known decentralized method used today is blockchain technology, which has been taken into consideration when creating the next generation of decentralized social platforms. This article also performs a systematic study and provides a summary of how fake news spreads in the real world, how it spreads in a decentralized system, and how the rumour block strategy functions. This article also covers a number of difficulties in implementing Blockchain in social media fake environments and suggests alternate approaches for implementation and further study.
Alexander Shevtsov, Despoina Antonakaki, Ioannis Lamprou, Ioannis Kontogiorgakis · 6 authors
On 24 February 2022, Russia invaded Ukraine, starting what is now known as the Russo-Ukrainian War, initiating an online discourse on social media. Twitter as one of the most popular SNs, with an open and democratic character, enables a transparent discussion among its large user base. Unfortunately, this often leads to Twitter's policy violations, propaganda, abusive actions, civil integrity violation, and consequently to user accounts' suspension and deletion. This study focuses on the Twitter suspension mechanism and the analysis of shared content and features of the user accounts that may lead to this. Toward this goal, we have obtained a dataset containing 107.7M tweets, originating from 9.8 million users, using Twitter API. We extract the categories of shared content of the suspended accounts and explain their characteristics, through the extraction of text embeddings in junction with cosine similarity clustering. Our results reveal scam campaigns taking advantage of trending topics regarding the Russia-Ukrainian conflict for Bitcoin and Ethereum fraud, spam, and advertisement campaigns. Additionally, we apply a machine learning methodology including a SHapley Additive explainability model to understand and explain how user accounts get suspended.
Disinformation and fake news are used by multiple actors to manipulate and influence the public with the purpose of gaining a series of advantages. This paper describes a promising solution to the increased spread of disinformation on the Internet. Our approach leverages blockchain technology combined with both crowd intelligence and federated artificial intelligence to develop efficient capabilities that address the disinformation phenomenon. The blockchain-based architecture of the platform creates a decentralized ecosystem that ensures transparency and trust, enabling the users to make correctly informed decisions in the face of disinformation. The key differentiating factor of the platform is the incorporation of both crowd and artificial intelligence in a system that can identify and respond to disinformation quickly and efficiently. The presented architecture can be used to build reactive and proactive platforms to effectively challenge disinformation.
Increasing public concerns about the environment have led to many studies that have explored current issues and approaches towards its protection. Much less studied, however, is topic of public opinion surrounding the impact that cryptocurrencies are having on the environment. The cryptocurrency market, in particular, bitcoin, currently rivals other top well-known assets such as precious metals and exchanged traded funds in market value, and its growing. This work examines public opinion expressed about the environmental impacts of bitcoin derived from Twitter feeds. Three primary research questions were addressed in this work related to topics of public interest, their location, and people and places involved. Our findings show that factions of of the public are interest in protecting the environment, with topics that resonate mainly related to energy. This discourse was also taking place at few similar locations with a mix of different people and places of interest.
Maria Ilaria Lunesu, Roberto Tonelli, Andrea Pinna, Simone Sansoni
Soulbound Tokens were introduced last May by Vitalik Buterin as a new kind of non-fungible, non-transferable token in the Ethereum ecosystem. The main idea behind such tokens is that they are born and die at the same address without ever changing ownership. Because there is typically no one-to-one correspondence between blockchain addresses and people, asserting that such new tokens are associated with a person for life is a strong assertion. Nevertheless, these new tokens promise to envision practical applications related to personal reputation or ownership of specific, non-transferable assets, and their real-world potential applications remain largely unexplored. In this paper, we present a practical application of such tokens, investigating a use case where a real-world problem largely impacting modern life has been exploited: COVID vaccine certification. The approach can easily be extended to other vaccination cases and relies on the use of a DApp where Soulbound Tokens have been implemented. In our scheme, two main actors are involved. The system administrator, represented by a local medical organization, is able to insert into a database the list of vaccines for which certification will be sent, and the citizen, after receiving the vaccination, will be able to receive and visualize the certifications provided by the first actor.
Md. Anisul Islam Mahmud, A. A. Talha Talukder, Arbiya Sultana, Kazi Iftesam Amin Bhuiyan · 7 authors
The growing popularity of online news has prompted concerns regarding (i) the socio-political influence over news dissemination, (ii) the waning freedom of news media, (iii) and a facile news evaluation process. A piece of news having the power to capture a large audience and sow the seed of bizarre consequences on a national scale should be prudently evaluated before reaching the mass. In quest of making a substantial profit, and sometimes due to inevitable socio-political influence, news with biased heading outpours mass media, resulting in ambiguity and mass manipulation. In this paper, we suggest a blockchain, smart contract, and incremental machine learning-based news evaluation procedure for the Bengali language to overcome these challenges. Weighted synthesis of machine classification and human expert opinion in a decentralized platform are synthesized to evaluate news. With continuous data, the Natural Language Processing (NLP) model is incrementally trained, and the best version of the model is used to detect deprived fake news. During experiments, the NLP model with initial training and testing accuracy of 84.94% and 84.99% was increased to 93.75% and 93.80% after nine rounds of incremental model training. On the Ethereum test network, the protocols have been installed and tested. The simulation demonstrates successful implementation of our proposed system.
Cryptocurrency is a speculative investment due to its volatility which could result in significant returns but also could end in crashes. Terra blockchain collapsed when its stable coin UST failed to maintain its peg to 1 USD and caused its sister coin LUNA to drop by more than 90% only in a few days. Terra LUNA itself has gained success and attracted many investors that became a strong community called Lunatics. Using Netnography; this study tried to observe crisis response strategies from Do Kwon, founder and CEO of Terraform Labs, and from Terra LUNA official Twitter account during the crash. Also, this study used community sentiment as an indicator to measure the success of the strategies. In addition, this study observed the interaction of the community during the crash period and how they overcome the crisis together. The results show that mortification and corrective action are the most effective strategy to generate positive sentiment. However, denials toward rumors cause more negative sentiment within the community. Despite the recovery plan from the Terra network, the Lunatics community also has its ways of recovering from the crisis. This study also revealed that community influencers' roles are crucial in controlling rumors during the crisis.
Abstract Event studies in general rely on having a high-quality curated database of events. In this paper we introduce CryptoGDelt2022, a news event dataset extracted from the Global Database of Events, Language and Tone (GDELT) containing more than 243 thousands cryptocurrency related news events between the 31st of March 2021 and 30th of April 2022. The dataset is enriched with supervised machine learning scores for Relevance, Sentiment and Strength. Supervised Relevance Score measures how related to Cryptocurrency the topic is using news web scrapped from Yahoo in general and from the Cryptocurrency part of the site, after a comparison of approaches; Latent Dirichlet Allocation (LDA), BERT and Naive Bayes, Naive Bayes was chosen and the hyper-parameter tuned model reached accuracy: 97.84 % in the train set and 91.70% in the test set. Supervised Sentiment Score measures the negative, neutral or positive tone of the news, after hyper-parameter tuning, the retrained FinBERT model achieved accuracy of 92.63% in the train set and 86.11% in the test set. Supervised Strength Score measures how strong the news by using the abnormal return using Fama French 3-factor model as target output variable, after hyper-parameter tuning, the trained Naive Bayes model reached accuracy of 63.34%. The work concludes that GDELT is more reliable source of event when compared to news selected from cryptocurrency specialized websites as it presents a more balanced positive and negative number of news. All data sets and Python Jupyter Notebooks are available in the project's GitHub.
Conspiracy theories are everywhere around us. Generating countless websites, books, films, series, and podcasts, and encompassing nearly every major negative event that has taken place since the end of World War II, conspiracies have become a phenomenon that anyone as a citizen and thinking individual has had to cope with in the last few decades, arguably reaching a peak during the Trump presidency, with the rise of QAnon and various conspiracy theories about the current Covid-19 pandemic (Barkun 2017; Amarasingam and Argentino 2020; Mitchell et al. 2020; Uscinski et al. 2020).Not surprisingly, the rise of conspiracy theories has also coincided with an increasing scholarly interest, especially within psychology and the social sciences, although studies of conspiracies in literature and film have also grown in number during the last two decades. What has been much less thoroughly researched, however, is how the hermeneutical and epistemological mechanisms that lie at the foundation of conspiracy theories—what I term “conspiracy thinking”—have sneaked into other forms of discourse, and especially those that are far removed from classic conspiratorial themes such as the New World Order, Freemasonry and the Illuminati, the JFK assassination, or even ufology. In other words: Can conspiracy thinking also be traced where there is no hidden or evident conspiracy? What are the consequences for our understanding of the texts that contain and disseminate such modes of thinking? And are the boundaries between a conspiratorial and a legitimate interpretation of a work of art or literature always clear-cut?The aim of this article is to study two contemporary examples of conspiracy thinking related to Henrik Ibsen's plays, and to show how these hermeneutical forms have sneaked into discourses—such as literature and drama, and the critical reflection on them—that in themselves do not have much to do with conspiracies. Although my study is limited to Ibsen, I claim that this example is just one of many that take place in contemporary readings of Western literature. For while blockbusters like Dan Brown's The Da Vinci Code (2003) have contributed to spreading conspiracy theories widely in literary form, there is also a flourishing literature that seeks to find encoded messages and secret layers of meaning in canonical literary works. Just to mention two famous examples, the same Brown's Inferno (2013) draws upon the long-standing tradition of conspiracy theories related to Dante's Divine Comedy, and the works of William Shakespeare have been subjected to a long series of conspiratorial readings, arguably reaching a peak—at least in a Norwegian context—with Erlend Loe's and Petter Amundsen's mashup of theories about Shakespeare's persona and the coded messages that the English dramatist allegedly left in his texts (Loe and Amundsen 2006). These theories, as extravagant as they may appear, have made their way to mainstream media through both books, films, and TV series, and have garnered considerable public attention.This article focuses on two case studies that have several features in common with the examples mentioned above. These are Hemmeligheten bak Peer Gynt (Benneche 2017; The Secret behind Peer Gynt, henceforth Hemmeligheten) a documentary film that was aired by the Norwegian Broadcasting Corporation (NRK) on the occasion of the 150th anniversary of the publication of the play, and Peer Gynt-koden (Larsen 2006; The Peer Gynt Code, henceforth Koden), a pseudoscientific book published by the Norwegian academic publisher Abstrakt Forlag on the occasion of the centennial of Ibsen's death. I will argue that the interpretations these works present, although apparently marginal and not particularly influential on Ibsen scholarship, are a product of the much larger international phenomenon of conspiracy theories. Studying them allows us to identify not only how conspiracy thinking has spread to mainstream discourse to such a degree that its recipients are not to that is at its also to a about the of interpretation that and may such case studies us the that canonical works of literature on conspiracy theories. is not and works of art that are the of such theories, of such as or readings aim at a that about a of our is and and The same be in the two examples in a that was Ibsen's Peer Gynt that the of such and that these through an academic and the mainstream this I will of as my I will the hermeneutical of and how is to the two examples mentioned above. 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Misleading content, fake news and false media spreading across social media platforms is a threat to society. It negatively effects people and its misuse in political propaganda, cyber crimes and other areas is undeniable. This paper presents how to build a secure, trustful and efficient platform to combat against malicious content and fake news by implementing NLP techniques including stop words removal, topic modelling and by applying machine learning models of KNN, Mulitnomial Naive Bayes and deep learning model of LSTM with Word2Vec and GloVe. These models are fed training and testing data by concatenating two kaggle datasets and selecting sample from them. Their accuracy is also compared at the end. To make the system decentralized Etheruem Blockchain is combined and as an offchain storage for blockchain IPFS is used.
Cryptocurrencies are highly speculative assets with large price volatility. If one could forecast their behavior, this would make them more attractive to investors. In this work we study the problem of predicting the future performance of cryptocurrencies using social media data. We propose a new model to measure the engagement of users with topics discussed on social media based on interactions with social media posts. This model overcomes the limitations of previous volume and sentiment based approaches. We use this model to estimate engagement coefficients for 48 cryptocurrencies created between 2019 and 2021 using data from Twitter from the first month of the cryptocurrencies' existence. We find that the future returns of the cryptocurrencies are dependent on the engagement coefficients. Cryptocurrencies whose engagement coefficients have extreme values have lower returns. Low engagement coefficients signal a lack of interest, while high engagement coefficients signal artificial activity which is likely from automated accounts known as bots. We measure the amount of bot posts for the cryptocurrencies and find that generally, cryptocurrencies with more bot posts have lower future returns. While future returns are dependent on both the bot activity and engagement coefficient, the dependence is strongest for the engagement coefficient, especially for short-term returns. We show that simple investment strategies which select cryptocurrencies with engagement coefficients exceeding a fixed threshold perform well for holding times of a few months.
In this paper we start from the assumption that social dynamics and cultural-civilizational progress cannot be viewed separately from the social history of the media as complex technological-communication structures. In this paper we deal with the influence of new disruptive technologies DLT (Distributed Ledger Technologies) better known as blockchain technologies which, thanks to the latest technological solutions, have great potential for transforming the media and journalism as a profession, thus we have explained the technological concept on which they are based. We will discuss the concept of personalized blockchain journalism and propose a user economy model that guarantees the financial sustainability of the platform. Observing information as a user experience, we have discussed the possibility of adequate cognitive response of users in conditions of information saturation, and raised the issue of structuring information in designing a journalistic platform on the blockchain, as an ecosystem that will distance itself from existing polluted media space. Finally, we have proposed a topic for further reflection and scientific research, which is the latest technological transition based on quantum computing, artificial intelligence and the Metaverse, which will provide a completely new user experience in 3D virtual space, where user avatars will rely less and less on traditional media and journalism as we know it today.
A distributed ledger, or block chain, provides safe and immutable storage. Through the use of cutting-edge information and communication technologies, e-governance enables for the interchange of information between the government and people or organizations. On the one hand, e-governance services provide efficient and quick access to treatment; on the other hand, they heighten the danger of privacy and security breaches. Without the need of a middleman, a blockchain-based e-governance system provides safe and transparent services. Fake news detection and recognition of sources of news has become a hot subject in the news business as well as on social media. Anyone may readily create or edit digital information and broadcast it on social networking networks in the digital age. On the one side, these social networking sites make modern-day communication more easier, but they’ve also introduced new problems to real-world application, such as the viral transmission of false information with malevolent intent. In this chapter, the authors highlight the role of blockchain in e-governance. Moreover, the applications of blockchain in tracing the fake news on social media are also discussed in this chapter.
The spread of deceptive or misleading information, commonly referred to as misinformation, poses a social, economic, and political threat. Such deceptive information spreads quickly and inexpensively. For example, with the hype around blockchain technologies, misinformation on “get rich quick” scams on the Web is rampant, as evidenced by sophisticated Twitter hacks of celebrities and many social media posts that bait unsuspecting users to visit phishing websites. Unfortunately, AI technologies have contributed to the growing pains of misinformation on the Web, with the advances in technologies such as generative adversarial deep learning techniques that can generate “deep fakes” for nefarious purposes. At the same time, researchers are working on a different set of AI technologies to combat misinformation, akin to “fighting fire with fire.” As there is no clear way to win the online “cat-and-mouse” game against fake news generators and spreaders of misinformation, we believe social media platforms could be fortified with blockchain and AI technologies to mitigate the extent of misinformation propagation in various communities worldwide. Tamper-proof blockchain techniques can provide irrefutable evidence of what content is authentic, guaranteeing how the information has evolved with provenance trails. Various AI models that could be used for detecting fake news can be served on a blockchain for the effective and transparent utility of the model. Such a synergistic combination of AI and blockchain is a burgeoning area of research. This paper outlines a proposal for combining blockchain and AI techniques for handling misinformation on the Web and highlights some of the early ongoing work in this space.
Blockchain technology is one of the emerging technologies of the decade. Immutability, reliability, and distributed ledger are the main features of the blockchain, making this technology very popular in the short time from its advent. The use of blockchain technology is not only restricted to the financial sector, but the healthcare sector is also focusing its attention on a blockchain. Immunization Programs can be assisted by blockchain technology to achieve reliability, security, and traceability. In this paper, we describe the blockchain-based reliable approach for the Immunization Program using the Hyperledger Fabric platform to provide a practical solution to the challenges of the current system. The system will maintain a real-time view of the vaccination record and provide a single integrated view of localized and diverse records. This united form of the data help the doctors for better diagnosis in case of disease, and specialists to make better strategic plans for Immunization.
Misinformation constitutes one of the main challenges to counter the infodemic: misleading news, even if not blatantly false, can cause harm especially in crisis scenarios such as the pandemic. Due to the fast proliferation of information across digital media, human fact-checkers struggle to keep up with fake news, while automatic fact-checkers are not able to identify the grey area of misinformation. We, thus, propose to reverse engineer the manipulation of information offering citizens the means to become their own fact-checkers through digital literacy and critical thinking. Through a corpus analysis of fact-checked news about COVID-19, we identify 10 fallacies–arguments which seem valid but are not–that systematically trigger misinformation and offer a systematic procedure to identify them. Next to fallacies, we examine the types of sources associated to (mis-/dis-)information in our dataset as well as the type of claims making up the headlines. The statistical patterns surfaced from these three levels of analysis reveal a misinformation ecosystem where no source type is exempt from flawed arguments with frequent evading the burden of proof and cherry picking behaviors, even when descriptive claims are at stake. In such a scenario, exercising the audience’s critical skills through fallacy and semantic analysis is necessary to guarantee fake news immunity.