AniAniWeb: A wiki approach to personal home pages

This article reports on my dissertation research on personal home pages. It focuses on the design of AniAniWeb, a server-based system for authoring personal home pages. AniAniWeb builds on a wiki foundation to address many of the limitations of static technologies used to author personal home pages. This article motivates the technical hypotheses behind AniAniWeb and reflects on these hypotheses, based on a two year study of adopters using AniAniWeb in academia, a prominent vocational setting where personal home pages are important. In particular, I reflect on two broad categories: 1) the usefulness of wiki features (wiki authoring, wiki mark-up, and interaction / collaboration) to authoring personal home pages; 2) the other features (structure, designing looks, and access control) needed to make a wiki approach to personal home pages viable

Around the table: Are multiple-touch surfaces better than single-touch for children's collaborative interactions?

This paper presents a classroom study that investigated the potential of using touch tabletop technology to support children's collaborative learning interactions. Children aged 7-10 worked in groups of three on a collaborative planning task in which they designed a seating plan for their classroom. In the single-touch condition, the tabletop surface allowed only one child to interact with the digital content at a time. In the multiple-touch condition, the children could interact with the digital content simultaneously. Results showed that touch condition did not affect the frequency or equity of interactions, but did influence the nature of children's discussion. In the multiple-touch condition, children talked more about the task; in the single-touch condition, they talked more about turn taking. We also report age and gender differences

Learning by doing with shareable interfaces

New technologies, such as multi-touch tables, increasingly provide shareable interfaces where multiple people can simultaneously interact, enabling co-located groups to collaborate more flexibly than using single personal computers. Soon, these technologies will make their way into the classroom. However, little is known about what kinds of learning activities they will effectively support that other technologies, such as mobile devices, whiteboards, and personal computers, are currently unable to do. We suggest that one of the most promising uses of shareable interfaces is to support learning through exploration and creation. We present our work on DigiTile as a case study of how shareable interfaces can enable these forms of learning by doing. We demonstrate how DigiTile supports collaboration, present a field study on its learning benefits, and show how it can fit into a larger computing ecology

On the Interplay of Subset Selection and Informed Graph Neural Networks

Machine learning techniques paired with the availability of massive datasets dramatically enhance our ability to explore the chemical compound space by providing fast and accurate predictions of molecular properties. However, learning on large datasets is strongly limited by the availability of computational resources and can be infeasible in some scenarios. Moreover, the instances in the datasets may not yet be labelled and generating the labels can be costly, as in the case of quantum chemistry computations. Thus, there is a need to select small training subsets from large pools of unlabelled data points and to develop reliable ML methods that can effectively learn from small training sets. This work focuses on predicting the molecules atomization energy in the QM9 dataset. We investigate the advantages of employing domain knowledge-based data sampling methods for an efficient training set selection combined with informed ML techniques. In particular, we show how maximizing molecular diversity in the training set selection process increases the robustness of linear and nonlinear regression techniques such as kernel methods and graph neural networks. We also check the reliability of the predictions made by the graph neural network with a model-agnostic explainer based on the rate distortion explanation framework

Next generation repositories: Scaling up repositories to a global knowledge commons

The current system for disseminating research, which is dominated by commercial publishers, is far from ideal. In an economic sense, prices for both subscriptions and APCs are over-inflated and will likely continue to rise at unacceptable rates. Additionally, there are significant inequalities in the international publishing system both in terms of access and participation. The incentives built into the system, which oblige researchers to publish in traditional publishing venues, perpetuate these problems and greatly stifle our ability to evolve and innovate. The Next Generation Repositories offers an alternative vision, “to position repositories as the foundation for a distributed, globally networked infrastructure for scholarly communication, on top of which layers of value-added services will be deployed, thereby transforming the system, making it more research-centric, open to and supportive of innovation, while also collectively managed by the scholarly community.” An important component of this vision is that repositories will provide access to a wide variety of research outputs, creating the conditions whereby a greater diversity of contributions to the scholarly record will be accessible, and also formally recognized in research assessment processes. This is very much is aligned with others strategic thinking, such as MIT’s Future of Libraries Report and Lorcan Dempsey’s notion of the “inside-out” library, that are defining a new role of libraries in the 21st century. This future involves a shift away from libraries purchasing content for their local users, towards libraries curating and sharing with the rest of the world the research outputs produced at their institution. However, to achieve this vision, we need to adopt new functionalities and technologies in repositories and build additional services such as standardized usage metrics, peer review and social networking on top of them. The Next Generation Repositories report provides recommendations for these new behaviours and technologies to move the vision forward. There are already several groups actively working on the adoption of these technologies and services, including OpenAIRE, National Institute of Informatics (Japan) and a US Implementers Group facilitated led by COAR. This paper will present the vision for next generation repositories, provide an overview of the conceptual model including the role of libraries and hubs that will offer services to the network of repositories. In addition, we will provide an overview of current activities to put the next generation repositories infrastructure and services in place

Next generation repositories: scaling up repositories to a global knowledge commons

The widespread deployment of repository systems in higher education and research institutions provides the foundation for a distributed, globally networked infrastructure for scholarly communication. However, repository platforms are still using technologies and protocols designed almost twenty years ago, before the boom of the Web and the dominance of Google, social networking, semantic web and ubiquitous mobile devices. This is, in large part, why repositories have not fully realized their potential. In April 2016, COAR launched the Next Generation Repositories Working Group to identify the core functionalities for the next generation of repositories, as well as the architectures and technologies required to implement them. In November 2017, the Working Group published a report defining 11 new behaviours, as well as the technologies, standards and protocols that will facilitate the development of new services on top of the collective network. This session will present the background and vision underlying this work, define the behaviours and technologies outlined in the report, and discuss the current activities being undertaken to implement the recommendations. It will also be an opportunity for the community to provide further input about next steps for these recommendations.info:eu-repo/semantics/publishedVersio

Private information arrival, trading activity, and price formation: Evidence from nonpublic merger negotiations

Abstract: We provide evidence on how stock prices and trading activity respond to the arrival of private information about firm value using the dates of material nonpublic merger negotiations to proxy for private information arrival. Target firm returns are 0.41% higher over two days following each nonpublic negotiation event. Trading volume, order imbalance, and trade size also spike in this window. Larger price reactions following negotiation events preempt deal announcement returns. The price response following negotiation events is explained by proxies for the expected profits and price impact of informed trading, prior press speculation, institutional ownership, and contemporaneous trading activity signals. We thank Linda Bamber, Diane Del Guercio, Ro Gutierrez, Kathy Kahle, Ron Kaniel, Eric Kelley, Chris Lamoureux, Jochen Lawrenz, Lubo Litov, Wayne Mikkelson, Bill Schwert, Rick Sias, Jerry Warner, and workshop participants at MIT, and the Universities of Arizona, Georgia, Innsbruck, Oregon, Rochester, and Utah for helpful comments. We are also grateful to Denis Sosyura (discussant) and participants at the 2012 University of Washington Summer Finance Conference. We recognize the excellent research assistance provided by Tyler Brough, Michael Dambra, Douglas Fairhurst, Jordan Neyland, and Matthew Serfling. * Rochester, NY 14627; phone: 585.273.4818; email: [email protected] ** Tucson, AZ 85721; phone: 520.621.8761; email: [email protected] 1 Understanding the degree to which investors rapidly acquire and trade on new private information about firm value and how their trades affect price formation is central to the design of securities regulation and inferences about the efficiency of financial markets. The evidence in a number of recent studies shows that informed investors obtain private information in a variety of ways, such as through connections to insiders, and that they use this information to make profitable trades. For instance, To infer private information-based trades, the aforementioned studies often begin with a firm's disclosure of earnings or the announcement of a merger agreement and examine trading behavior and price movements over a brief window before the disclosure. But, ascertaining whether connected investors trade on private information is challenging in part due to the difficulty of tying stock returns and trading decisions to the underlying arrival of private information. Because securities regulation does not generally compel managers to disclose material nonpublic information immediately, traders can acquire and exploit private information weeks or months before the firm is required to disclose it. In this paper we study underlying events that produce and distribute private information about the value of a firm. Specifically, we use the dates of merger negotiations that occur privately, but are disclosed weeks or months after the deal is announced, to more precisely identify when private information is actually generated. These data allow us to examine whether informed investors promptly trade on private information that arrives during the course of merger 2 negotiations and if their trading has an economically important effect on target firms' stock prices. 1 For a sample of 545 completed acquisitions announced between 1995 and 2006, we use Securities and Exchange Commission (SEC)-mandated background disclosures to identify the dates and types of various material "events" that occur during negotiations between the target and potential acquirers before an acquisition deal is announced. These nonpublic negotiation events include, for example, the initiation of merger talks, a bidder making a private offer for the target, the retention of a financial advisor, or a meeting of the target's board to evaluate a proposed deal. On average, over the three months prior to the merging parties' disclosure of a preliminary merger agreement (hereafter, referred to as the deal announcement), there are about seven unique trading days during which at least one material negotiation event occurs. After controlling for the impact of press speculation about a potential acquisition deal (which affects 18% of the deals in our sample) we find that for each nonpublic negotiation event, target firm excess abnormal returns average 0.18% the same day and 0.23% the day after the event, resulting in a two-day estimated excess return of 0.41%. These returns are incremental to the average positive abnormal returns during the negotiation period and thus provide a lower-bound estimate of the price impact of trading on private information about merger negotiations. To more fully understand the source of these returns, we examine whether non-price measures of informed trading are also related to the arrival of private information during merger negotiations. We document significant spikes in abnormal trading volume, buyer-initiated transactions measured by order imbalance, and medium-size trades over the two-day window following a nonpublic negotiation event. Moreover, we also find that increases in contemporaneous 1 Informed trading before a merger announcement includes both illegal insider trading on material nonpublic information and legitimate trading based on superior information acquisition and processing. Moreover, the term "insider" in insider trading as used in this paper refers to any individual that knowingly trades on material nonpublic information. This could include, but is not limited to, corporate insiders as defined under Section 16 requirements for reporting trades (e.g., officers, directors, and some blockholders). See Agrawal and Jaffe (1995) and Agrawal and Nasser (2012) for evidence on trading by corporate insiders prior to merger announcements. 3 volume, buy-sell order imbalance, and medium-size trades predict stock returns following negotiation events. For example, a ten percentage point increase in abnormal trading volume is associated with a 12 basis point larger stock price reaction to each negotiation event. These effects are incremental to the typical effect of trading activity on stock returns and suggest that the arrival of private information about merger negotiations has substantive implications for understanding the trading decisions of informed investors and the informational efficiency of stock prices. Next, we investigate whether firm and deal-specific factors explain how quickly target stock prices respond to the arrival of private information. We show that stock returns following negotiation events are increasing in both the expected profits from trading on private information, as measured by the offer premium, and the likelihood of deal completion, captured by a tender offer or target termination fee clause. We further document that the magnitude of the stock price response is increasing in the adverse selection costs of trading in the target firm's shares, proxied by PIN (probability of informed trading) and low analyst coverage. In other words, stock returns are more sensitive to negotiation events for firms whose stock price is generally more sensitive to informed trades. We also find that higher institutional ownership is associated with a decrease in the sensitivity of stock returns to negotiation events. This evidence suggests that institutions may be less willing than individuals to trade on private information from negotiation events or that if they do trade on this information, they do not do so immediately after a negotiation event. We also examine whether media speculation about a deal is related to the sensitivity of target firm stock returns to nonpublic negotiation events. Controlling for the market's reaction to a rumor, we show that for the 18% of the deals in our sample with at least one published rumor prior to the deal announcement, the target firm's stock returns respond significantly more to negotiation events. Further, we document that this effect is most pronounced for nonpublic negotiation events that occur after the rumor is published. These findings are consistent with the conventional wisdom that 4 the litigation risk from trading on private information is decreasing in the amount of existing public information about a potential deal and with the notion that because press speculation increases target firms' stock return volatility, news rumors make it easier for informed investors to trade without detection from other traders. We investigate the factors that determine the timing and occurrence of press speculation. Indicating that private information from merger negotiations is in some instances quickly leaked to the media, we show that although press rumors tend to follow observable abnormal stock returns and trading volume, they are incrementally more likely to take place over the two days following a nonpublic negotiation event. Further, implying that informed investors are potentially responsible for at least some of this leakage, we find that a deal is more likely to be rumored when the set of investors with private information about deal negotiations is larger, proxied for with measures for the number of deal insiders (Acharya and Johnson One interpretation of this finding is that, at times, informed investors intentionally leak some of their private information to the press so they can more easily trade on the remainder of their information. To further assess the economic importance of informed trading following the arrival of private information, we examine the extent to which the price impact of this trading affects the target's acquisition price and the market's reaction to the announcement of a merger agreement. Schwert's (1996) evidence suggests that for every 1 increase in the target's stock price prior to the deal announcement, the target negotiates more than a 1 increase in the final acquisition price from the acquirer. However, acquirers and targets know the dates they negotiated, and thus, acquirers should be able to discount stock price movements occurring just after negotiation events. Our results suggest that a $1 increase in stock price attributable to informed trading following nonpublic negotiation events leads to a$0.81 increase in the final transaction price, a significant 29% discount from the $1.14 increase in the final transaction price for each$1 of non-event price increase. In 5 other words, deal negotiators place a lower weight on stock returns linked to nonpublic negotiation event days than stock returns on other days. We also find that a one percent increase in the target's stock price attributable to informed trading following nonpublic negotiation events reduces the market's reaction to the deal announcement by 26 basis points. However, a similar one percent increase in stock price during the period prior to the deal announcement that is not attributable to negotiation events reduces the market's reaction by only 13 basis points. These findings imply that private information-based trading following merger negotiations is economically important in preempting the information in the deal announcement. Our study contributes to the literature that considers how public and private information impacts trading decisions and price formation. We use a novel but intuitive approach to provide insights on private information-based trading and its impact on price formation by focusing on the dates when private information is created. Our evidence indicates that well-informed traders rapidly exploit their information advantage. Their trades are reflected in volume, order flow, and trade size, and have an economically important effect on a firm's stock price. Further, we identify several factors that determine the magnitude of the stock price reaction to the arrival of private information during merger negotiations. The stock price reaction depends on contemporaneous volume and order flow, expected profits from trading on private information, the expected price impact of informed trading, institutional ownership, and whether a private negotiation event is preceded by press speculation. Implying that informed trading following merger negotiations preempts information in the deal announcement, we also show that stock returns linked to days with private information events are associated with significantly smaller deal announcement returns. This study also contributes to the emerging literature on how traders' characteristics and connections to insiders impact the timing and profitability of their trades and the efficiency of stock 6 prices. Our focus on days when information is produced and distributed provides an avenue for future research to examine how the trades of specific investors correlate with the arrival of private information. Given that we document trading activity and stock returns respond quickly to the arrival of new private information about firm value, our evidence also speaks to the SEC's focus on hedge funds, brokerages, deal advisers, and exchange traders and their access to and use of confidential inside information. The remainder of the paper is organized as follows. Section 1 reviews prior work on private information-based trading and discusses the potential for such trading activity subsequent to merger negotiations. Section 2 presents our empirical results. Section 3 concludes. Informed Trading and the Timing of Nonpublic Merger Negotiations Asymmetric information is a pervasive trait of capital markets. The intent of disclosure regulation is to ensure that material information is disclosed to investors, but there are few mandatory obligations for real-time disclosure of new information. As a result, stock prices can diverge from their full information value. Public disclosure of material nonpublic information may be delayed for weeks or even months, thereby providing incentives for traders to uncover private information. Traders with more precise information about a firm's value are more likely to trade on their information. In the absence of public disclosure of new information, the speed at which price converges to its full information value depends on informed trading. Profit-maximizing informed traders have incentives to camouflage their trades by spreading them out over time As the number of privately-informed investors grows, competition between them can create incentives to trade more aggressively, leading to more efficient prices (Holden and Subrahmanyam 7 (1992)). In contrast, 2 We focus on the timing of nonpublic merger negotiations to identify informed trading activity and its effect on price formation. 3 An informed investor's trading incentives depend on how negotiations progress, the expected offer price relative to the current price (the premium), and the likelihood of a successful deal. The distribution of that private information during negotiations also matters. The initial contact between the merging parties is often between CEOs and a few close advisors and directors. As discussions progress, the target's (and often the acquirer's) entire board is informed, financial and legal advisors are retained, investment bankers are contacted to assist with financing, and lower-level managers and auditors are brought in to support the due diligence process and integration planning. While the negotiating managers, directors, advisors, and financing 2 Prior studies that attempt to link trading on private information prior to acquisitions with target stock price formation look at the magnitude of stock price runups in acquisition targets 5 4 Expert networks are one of the interesting targets of recent insider trading investigations. Expert networks retain current and past managers and other industry specialists as consultants to investors such as mutual funds and hedge funds. While expert network firms have policies that bar their consultants from passing along confidential information, it appears that many consultants have done so. A recent complaint filed by the SEC alleges that ten consultants and one investment advisor working for the expert network firm Primary Global Research (PGR) passed along material nonpublic information to hedge funds and other PGR clients in exchange for cash compensation. The SEC alleges that the clients of PGR earned about $30 million in illicit profits as a result (SEC vs. Longria et a