How Polarized Have We Become? A Multimodal Classification of Trump Followers and Clinton Followers

Polarization in American politics has been extensively documented and analyzed for decades, and the phenomenon became all the more apparent during the 2016 presidential election, where Trump and Clinton depicted two radically different pictures of America. Inspired by this gaping polarization and the extensive utilization of Twitter during the 2016 presidential campaign, in this paper we take the first step in measuring polarization in social media and we attempt to predict individuals' Twitter following behavior through analyzing ones' everyday tweets, profile images and posted pictures. As such, we treat polarization as a classification problem and study to what extent Trump followers and Clinton followers on Twitter can be distinguished, which in turn serves as a metric of polarization in general. We apply LSTM to processing tweet features and we extract visual features using the VGG neural network. Integrating these two sets of features boosts the overall performance. We are able to achieve an accuracy of 69%, suggesting that the high degree of polarization recorded in the literature has started to manifest itself in social media as well.Comment: 16 pages, SocInfo 2017, 9th International Conference on Social Informatic

A Layered Software Architecture for the Management of a Manufacturing Company

In this paper we describe a layered software architecture in the management of a manufactur-ing company that intensively uses computer technology. Application tools, new and legacy, after the updating, operate in a context of an open web oriented architecture. The software architecture enables the integration and interoperability among all tools that support business processes. Manufacturing Executive System and Text Mining tools are excellent interfaces, the former both for internal production and management processes and the latter for external processes coming from the market. In this way, it is possible to implement, a computer integrated factory, flexible and agile, that immediately responds to customer requirements.ICT, Service Oriented Architecture, Web Services, Computer-Integrated Factory, Application Software

Credit Card Fraud: A New Perspective On Tackling An Intransigent Problem

This article offers a new perspective on battling credit card fraud. It departs from a focus on post factum liability, which characterizes most legal scholarship and federal legislation on credit card fraud and applies corrective mechanisms only after the damage is done. Instead, this article focuses on preempting credit card fraud by tackling the root causes of the problem: the built-in incentives that keep the credit card industry from fighting fraud on a system-wide basis. This article examines how credit card companies and banks have created a self-interested infrastructure that insulates them from the liabilities and costs of credit card fraud. Contrary to widespread belief, retailers, not card companies or banks, absorb much of the loss caused by thieves who shop with stolen credit cards. Also, credit card companies and banks earn fees from every credit card transaction, including those that are fraudulent. In addressing these problems, this article advocates broad reforms, including legislation that would mandate data security standards for the industry, empower multiple stakeholders to create the new standards, and offer companies incentives to comply by capping bank fees for those that are compliant, while deregulating fees for those that are not compliant

Blockchain For Food: Making Sense of Technology and the Impact on Biofortified Seeds

The global food system is under pressure and is in the early stages of a major transition towards more transparency, circularity, and personalisation. In the coming decades, there is an increasing need for more food production with fewer resources. Thus, increasing crop yields and nutritional value per crop is arguably an important factor in this global food transition. Biofortification can play an important role in feeding the world. Biofortified seeds create produce with increased nutritional values, mainly minerals and vitamins, while using the same or less resources as non-biofortified variants. However, a farmer cannot distinguish a biofortified seed from a regular seed. Due to the invisible nature of the enhanced seeds, counterfeit products are common, limiting wide-scale adoption of biofortified crops. Fraudulent seeds pose a major obstacle in the adoption of biofortified crops. A system that could guarantee the origin of the biofortified seeds is therefore required to ensure widespread adoption. This trust-ensuring immutable proof for the biofortified seeds, can be provided via blockchain technology

Understanding Chat Messages for Sticker Recommendation in Messaging Apps

Stickers are popularly used in messaging apps such as Hike to visually express a nuanced range of thoughts and utterances to convey exaggerated emotions. However, discovering the right sticker from a large and ever expanding pool of stickers while chatting can be cumbersome. In this paper, we describe a system for recommending stickers in real time as the user is typing based on the context of the conversation. We decompose the sticker recommendation (SR) problem into two steps. First, we predict the message that the user is likely to send in the chat. Second, we substitute the predicted message with an appropriate sticker. Majority of Hike's messages are in the form of text which is transliterated from users' native language to the Roman script. This leads to numerous orthographic variations of the same message and makes accurate message prediction challenging. To address this issue, we learn dense representations of chat messages employing character level convolution network in an unsupervised manner. We use them to cluster the messages that have the same meaning. In the subsequent steps, we predict the message cluster instead of the message. Our approach does not depend on human labelled data (except for validation), leading to fully automatic updation and tuning pipeline for the underlying models. We also propose a novel hybrid message prediction model, which can run with low latency on low-end phones that have severe computational limitations. Our described system has been deployed for more than $6$ months and is being used by millions of users along with hundreds of thousands of expressive stickers

From Curved Bonding to Configuration Spaces

Bonding curves are continuous liquidity mechanisms which are used in market design for cryptographically-supported token economies. Tokens are atomic units of state information which are cryptographically verifiable in peer-to-peer networks. Bonding curves are an example of an enforceable mechanism through which participating agents influence this state. By designing such mechanisms, an engineer may establish the topological structure of a token economy without presupposing the utilities or associated actions of the agents within that economy. This is accomplished by introducing configuration spaces, which are proper subsets of the global state space representing all achievable states under the designed mechanisms. Any global properties true for all points in the configuration space are true for all possible sequences of actions on the part of agents. This paper generalizes the notion of a bonding curve to formalize the relationship between cryptographically enforced mechanisms and their associated configuration spaces, using invariant properties of conservation functions. We then proceed to apply this framework to analyze the augmented bonding curve design, which is currently under development by a project in the non-profit funding sector.Series: Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Researc

Free Money, But Not Tax-Free: A Proposal for the Tax Treatment of Cryptocurrency Hard Forks

Cryptocurrency has attracted extraordinary attention as one of the greatest financial innovations in recent years. Equally noticeable are the increasingly frequent cryptocurrency events, such as hard forks. Put simply, a cryptocurrency hard fork happens when a single cryptocurrency splits in two, which results in original coin owners receiving free forked coins. Such hard forks have resulted in billions of dollars distributed to U.S. taxpayers. Despite ongoing regulatory efforts, to date, the Internal Revenue Service (IRS) has yet to take a clear position on the tax treatment of cryptocurrency hard forks. The lack of useful guidance when filing tax returns has left taxpayers genuinely confused in the past few years. To fill this regulatory gap, this Note proposes a framework for cryptocurrency hard fork taxation. It explains the underlying technology of cryptocurrency hard forks, examines the recommended guidelines from the American Bar Association and the Association of International Certified Professional Accountants on cryptocurrency hard fork taxation, and references the current practices in Japan and the United Kingdom to lay a solid foundation for the proposed framework. Ultimately, this Note proposes a two-pronged tax on cryptocurrency hard forks. The first tax is levied on the profit made from the receipt of forked coins, and the second tax is levied on the profit made from the disposition of forked coins. A concrete proposal is provided for the applicable coin valuation, tax basis, holding period, and tax rate for the two prongs. Aiming to propose a tax treatment that is closest to the nature of cryptocurrency hard forks, this proposal considers various practical concerns, such as the inefficiency of the cryptocurrency market, the indirect possession of forked coins through third-party exchanges, and the fluctuating trading prices of forked coins when determining the valuation, tax basis, and holding period. This proposal not only provides clarity for taxpayers in filing tax returns and fulfilling tax obligations, but it also relieves the potential tax deferral and tax evasion problems that arise after a cryptocurrency hard fork