자연주의적 탐구조사(Naturalistic Inquiry)

NUDGE: IMPROVING DECISIONS ABOUT HEALTH, WEALTH, AND HAPPINESS by Richard H. Thaler and Cass R. Sunstein Penguin Books, 2009, 312 pp, ISBN 978-0-14-311526-7This book is best described formally as a general explanation of and advocacy for libertarian paternalism, a term coined by the authors in earlier publications. Informally, it is about how leaders, systems, organizations, and governments can nudge people to do the things the nudgers want and need done for the betterment of the nudgees, or of society. It is paternalism in the sense that "it is legitimate for choice architects to try to influence people's behavior in order to make their lives longer, healthier, and better", (p. 5) It is libertarian in that "people should be free to do what they like - and to opt out of undesirable arrangements if they want to do so", (p. 5) The built-in possibility of opting out or making a different choice preserves freedom of choice even though people's behavior has been influenced by the nature of the presentation of the information or by the structure of the decisionmaking system. I had never heard of libertarian paternalism before reading this book, and I now find it fascinating.Written for a general audience, this book contains mostly social and behavioral science theory and models, but there is considerable discussion of structure and process that has roots in mathematical and quantitative modeling. One of the main applications of this social system is economic choice in investing, selecting and purchasing products and services, systems of taxes, banking (mortgages, borrowing, savings), and retirement systems. Other quantitative social choice systems discussed include environmental effects, health care plans, gambling, and organ donations. Softer issues that are also subject to a nudge-based approach are marriage, education, eating, drinking, smoking, influence, spread of information, and politics. There is something in this book for everyone.The basis for this libertarian paternalism concept is in the social theory called "science of choice", the study of the design and implementation of influence systems on various kinds of people. The terms Econs and Humans, are used to refer to people with either considerable or little rational decision-making talent, respectively. The various libertarian paternalism concepts and systems presented are tested and compared in light of these two types of people. Two foundational issues that this book has in common with another book, Network of Echoes: Imitation, Innovation and Invisible Leaders, that was also reviewed for this issue of the Journal are that 1 ) there are two modes of thinking (or components of the brain) - an automatic (intuitive) process and a reflective (rational) process and 2) the need for conformity and the desire for imitation are powerful forces in human behavior. …

Nudge: Improving Decisions about Health, Wealth, and Happiness

Over the past few years, there has been an increased interest in automatic facial behavior analysis and understanding. We present OpenFace 2.0 - a tool intended for computer vision and machine learning researchers, affective computing community and people interested in building interactive applications based on facial behavior analysis. OpenFace 2.0 is an extension of OpenFace toolkit and is capable of more accurate facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation. The computer vision algorithms which represent the core of OpenFace 2.0 demonstrate state-of-the-art results in all of the above mentioned tasks. Furthermore, our tool is capable of real-time performance and is able to run from a simple webcam without any specialist hardware. Finally, unlike a lot of modern approaches or toolkits, OpenFace 2.0 source code for training models and running them is freely available for research purposes.

https://par.nsf.gov/servlets/purl/10099458

OpenFace 2.0: Facial Behavior Analysis Toolkit

A rumor is commonly defined as a statement whose true value is unverifiable. Rumors may spread misinformation (false information) or disinformation (deliberately false information) on a network of people. Identifying rumors is crucial in online social media where large amounts of information are easily spread across a large network by sources with unverified authority. In this paper, we address the problem of rumor detection in microblogs and explore the effectiveness of 3 categories of features: content-based, network-based, and microblog-specific memes for correctly identifying rumors. Moreover, we show how these features are also effective in identifying disinformers, users who endorse a rumor and further help it to spread. We perform our experiments on more than 10,000 manually annotated tweets collected from Twitter and show how our retrieval model achieves more than 0.95 in Mean Average Precision (MAP). Finally, we believe that our dataset is the first large-scale dataset on rumor detection. It can open new dimensions in analyzing online misinformation and other aspects of microblog conversations.

/pdf/rumor-has-it-identifying-misinformation-in-microblogs-2viggs0li4.pdf

Rumor has it: Identifying Misinformation in Microblogs

The microblogging site Twitter generates a constant stream of communication, some of which concerns events of general interest. An analysis of Twitter may, therefore, give insights into why particular events resonate with the population. This article reports a study of a month of English Twitter posts, assessing whether popular events are typically associated with increases in sentiment strength, as seems intuitively likely. Using the top 30 events, determined by a measure of relative increase in (general) term usage, the results give strong evidence that popular events are normally associated with increases in negative sentiment strength and some evidence that peaks of interest in events have stronger positive sentiment than the time before the peak. It seems that many positive events, such as the Oscars, are capable of generating increased negative sentiment in reaction to them. Nevertheless, the surprisingly small average change in sentiment associated with popular events (typically 1% and only 6% for Tiger Woods' confessions) is consistent with events affording posters opportunities to satisfy pre-existing personal goals more often than eliciting instinctive reactions. © 2011 Wiley Periodicals, Inc.

/pdf/sentiment-in-twitter-events-3zwbl6ba6l.pdf

Sentiment in Twitter events

Users on Twitter, a microblogging service, started the phenomenon of adding tags to their messages sometime around February 2008. These tags are distinct from those in other Web 2.0 systems because users are less likely to index messages for later retrieval. We compare tagging patterns in Twitter with those in Delicious to show that tagging behavior in Twitter is different because of its conversational, rather than organizational nature. We use a mixed method of statistical analysis and an interpretive approach to study the phenomenon. We find that tagging in Twitter is more about filtering and directing content so that it appears in certain streams. The most illustrative example of how tagging in Twitter differs is the phenomenon of the Twitter micro-meme: emergent topics for which a tag is created, used widely for a few days, then disappears. We describe the micro-meme phenomenon and discuss the importance of this new tagging practice for the larger real-time search context.

/pdf/conversational-tagging-in-twitter-xhduvg3lkj.pdf

Conversational tagging in twitter

Users frequently modify a previous search query in hope of retrieving better results. These modifications are called query reformulations or query refinements. Existing research has studied how web search engines can propose reformulations, but has given less attention to how people perform query reformulations. In this paper, we aim to better understand how web searchers refine queries and form a theoretical foundation for query reformulation. We study users' reformulation strategies in the context of the AOL query logs. We create a taxonomy of query refinement strategies and build a high precision rule-based classifier to detect each type of reformulation. Effectiveness of reformulations is measured using user click behavior. Most reformulation strategies result in some benefit to the user. Certain strategies like add/remove words, word substitution, acronym expansion, and spelling correction are more likely to cause clicks, especially on higher ranked results. In contrast, users often click the same result as their previous query or select no results when forming acronyms and reordering words. Perhaps the most surprising finding is that some reformulations are better suited to helping users when the current results are already fruitful, while other reformulations are more effective when the results are lacking. Our findings inform the design of applications that can assist searchers; examples are described in this paper.

/pdf/analyzing-and-evaluating-query-reformulation-strategies-in-v1r6y5sjzt.pdf

Analyzing and evaluating query reformulation strategies in web search logs

Understanding how people interact with search engines is important in improving search quality. Web search engines typically analyze queries and clicked results, but these actions provide limited signals regarding search interaction. Laboratory studies often use richer methods such as gaze tracking, but this is impractical at Web scale. In this paper, we examine mouse cursor behavior on search engine results pages (SERPs), including not only clicks but also cursor movements and hovers over different page regions. We: (i) report an eye-tracking study showing that cursor position is closely related to eye gaze, especially on SERPs; (ii) present a scalable approach to capture cursor movements, and an analysis of search result examination behavior evident in these large-scale cursor data; and (iii) describe two applications (estimating search result relevance and distinguishing good from bad abandonment) that demonstrate the value of capturing cursor data. Our findings help us better understand how searchers use cursors on SERPs and can help design more effective search systems. Our scalable cursor tracking method may also be useful in non-search settings.

/pdf/no-clicks-no-problem-using-cursor-movements-to-understand-50495wekc3.pdf

No clicks, no problem: using cursor movements to understand and improve search

Video games are primarily designed for the players. However, video game spectating is also a popular activity, boosted by the rise of online video sites and major gaming tournaments. In this paper, we focus on the spectator, who is emerging as an important stakeholder in video games. Our study focuses on Starcraft, a popular real-time strategy game with millions of spectators and high level tournament play. We have collected over a hundred stories of the Starcraft spectator from online sources, aiming for as diverse a group as possible. We make three contributions using this data: i) we find nine personas in the data that tell us who the spectators are and why they spectate; ii) we strive to understand how different stakeholders, like commentators, players, crowds, and game designers, affect the spectator experience; and iii) we infer from the spectators' expressions what makes the game entertaining to watch, forming a theory of distinct types of information asymmetry that create suspense for the spectator. One design implication derived from these findings is that, rather than presenting as much information to the spectator as possible, it is more important for the stakeholders to be able to decide how and when they uncover that information.

Starcraft from the stands: understanding the game spectator

Past studies of user behavior in Web search have correlated eye-gaze and mouse cursor positions, and other lines of research have found cursor interactions to be useful in determining user intent and relevant parts of Web pages. However, cursor interactions are not all the same; different types of cursor behavior patterns exist, such as reading, hesitating, scrolling and clicking, each of which has a different meaning. We conduct a search study with 36 subjects and 32 search tasks to determine when gaze and cursor are aligned, and thus when the cursor position is a good proxy for gaze position. We study the effect of time, behavior patterns, user, and search task on the gaze-cursor alignment, findings which lead us to question the maxim that "gaze is well approximated by cursor." These lessons inform an experiment in which we predict the gaze position with better accuracy than simply using the cursor position, improving the state-of-the-art technique for approximating visual attention with the cursor. Our new technique can help make better use of large-scale cursor data in identifying how users examine Web search pages.

/pdf/user-see-user-point-gaze-and-cursor-alignment-in-web-search-xkdw1ypedr.pdf

Jeff Huang

Papers

Conversational tagging in twitter

Analyzing and evaluating query reformulation strategies in web search logs

No clicks, no problem: using cursor movements to understand and improve search

Starcraft from the stands: understanding the game spectator

User see, user point: gaze and cursor alignment in web search