Seeking out non-public information : sell-side analysts and the freedom of information act

A number of sell-side healthcare analysts gain access to information outside the purview of management through Freedom of Information Act requests to the Food and Drug Administration for records on factory inspections, complaints, and drug and medical device applications. Using a difference-in-differences methodology, we find that buy (sell) recommendations and upgrades (downgrades) earn higher (lower) stock returns over the year following the receipt of FDA records. We also examine the type of information revealed in FDA factory inspection reports, and find that analysts are less likely to downgrade and are less pessimistic in their recommendations than the consensus recommendation when the information contained in the FDA report is not particularly severe. Our findings are consistent with a subset of analysts utilizing non-public information channels independent of management to gain value-relevant information about their covered firms

Abductive retrieval for multimedia information seeking

In this paper we discuss an approach to the retrieval of data annotated using the MPEG-7 multimedia description schema. In particular we describe a framework for the retrieval of annotated video samples that is based on principles from the area of abductive reasoning

Seeking alcohol information on the Internet

It has been argued that people may be more willing to seek potentially threatening information on the Internet than they would in ‘real life’ (Joinson and Banyard, 2002). For alcohol drinkers, potentially threatening information includes diagnostic information on the amount they drink, and information about the negative effects of alcohol consumption. In the present study, participants with varying levels of alcohol intake and plans for change chose four alcohol-related articles to read (from twelve) using either the world-wide web (WWW) or pen and paper. Results showed that drinkers not currently reducing their drinking were more likely to seek diagnostic, potentially threatening anti-drinking information via the WWW compared to when seeking paper-based information. Drinkers either contemplating or engaging in efforts to reduce their drinking sought pro-drinking information on the WWW, and anti-drinking information when using pen and paper. The potential role of the Internet, and perceived anonymity, in health promotion is discussed

Evaluating Collaborative Information Seeking Interfaces with a Search-Oriented Inspection Method and Re-framed Information Seeking Theory

Despite the many implicit references to the social contexts of search within Information Seeking and Retrieval research, there has been relatively little work that has specifically investigated the additional requirements for collaborative information seeking interfaces. Here, we re-assess a recent analytical inspection framework, designed for individual information seeking, and then apply it to evaluate a recent collaborative information seeking interface: SearchTogether. The framework was built upon two models of solitary information seeking, and so as part of the re-assessment we first re-frame the models for collaborative contexts. We re-frame a model of search tactics, providing revised definitions that consider known collaborators. We then re-frame a model of user profiles to analyse support for different group dynamics. After presenting an analysis of SearchTogether, we reflect on its accuracy, showing that the framework identified 8 known truths, 8 new insights, and no known-to-be-untrue insights into the design. We conclude that the framework a) can still be applied to collaborative information seeking interfaces; b) can successfully produce additional requirements for collaborative information seeking interfaces; and c) can successfully model different dynamics of collaborating searchers

Workshop on web information seeking and interaction

The World Wide Web has provided access to a diverse range of information sources and systems. People engaging with this rich network of information may need to interact with different technologies, interfaces, and information providers in the course of a single search task. These systems may offer different interaction affordances and require users to adapt their informationseeking strategies. Not only is this challenging for users, but it also presents challenges for the designers of interactive systems, who need to make their own system useful and usable to broad user groups. The popularity of Web browsing and Web search engines has given rise to distinct forms of information-seeking behaviour, and new interaction styles, but we do not yet fully understand these or their implications for the development of new systems

Investigating the information-seeking behaviour of academic lawyers: From Ellis's model to design.

Information-seeking is important for lawyers, who have access to many dedicated electronic resources.However there is considerable scope for improving the design of these resources to better support information-seeking. One way of informing design is to use information-seeking models as theoretical lenses to analyse users’ behaviour with existing systems. However many models, including those informed by studying lawyers, analyse information-seeking at a high level of abstraction and are only likely to lead to broad-scoped design insights. We illustrate that one potentially useful (and lowerlevel) model is Ellis’s - by using it as a lens to analyse and make design suggestions based on the information-seeking behaviour of twenty-seven academic lawyers, who were asked to think aloud whilst using electronic legal resources to find information for their work. We identify similar information-seeking behaviours to those originally found by Ellis and his colleagues in scientific domains, along with several that were not identified in previous studies such as ‘updating’ (which we believe is particularly pertinent to legal information-seeking). We also present a refinement of Ellis’s model based on the identification of several levels that the behaviours were found to operate at and the identification of sets of mutually exclusive subtypes of behaviours

Using History to Study Information Seeking Behavior

has focused on approaches that provide a snapshot in time of what is going on in a household. This poster explores the use of history to examine changes over time in both information questions and information sources used in the prosecution of everyday life activities in America. The study is based on identifying endogenous and exogenous forces to the activity at hand, and seeing how these forces cause change. A secondary question raised in this poster is the largely unexamined belief that the Internet has played an exceptional role in changing the nature of everyday information seeking behavior in America. The case of 100 years of car buying in America is used as a particular example, drawn from a larger study of nine everyday American activities

User Intent Prediction in Information-seeking Conversations

Conversational assistants are being progressively adopted by the general population. However, they are not capable of handling complicated information-seeking tasks that involve multiple turns of information exchange. Due to the limited communication bandwidth in conversational search, it is important for conversational assistants to accurately detect and predict user intent in information-seeking conversations. In this paper, we investigate two aspects of user intent prediction in an information-seeking setting. First, we extract features based on the content, structural, and sentiment characteristics of a given utterance, and use classic machine learning methods to perform user intent prediction. We then conduct an in-depth feature importance analysis to identify key features in this prediction task. We find that structural features contribute most to the prediction performance. Given this finding, we construct neural classifiers to incorporate context information and achieve better performance without feature engineering. Our findings can provide insights into the important factors and effective methods of user intent prediction in information-seeking conversations.Comment: Accepted to CHIIR 201