Vcs Aim to Out-Angel the Angels
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
THE TRUTH CAN CATCH the LIE: the FLAWED UNDERSTANDING of ONLINE SPEECH in INRE Anonymous ONLINE SPEAKERS Musetta Durkeet
THE TRUTH CAN CATCH THE LIE: THE FLAWED UNDERSTANDING OF ONLINE SPEECH IN INRE ANoNYMous ONLINE SPEAKERS Musetta Durkeet In the early years of the Internet, many cases seeking disclosure of anonymous online speakers involved large companies seeking to unveil identities of anonymous posters criticizing the companies on online financial message boards.' In such situations, Internet service providers (ISPs)-or, less often, online service providers (OSPs)2-- disclosed individually- identifying information, often without providing defendants notice of this disclosure,' and judges showed hostility towards defendants' motions to quash.4 Often these subpoenas were issued by parties alleging various civil causes of action, including defamation and tortious interference with business contracts.s These cases occurred in a time when courts and the general public alike pictured the Internet as a wild west-like "frontier society,"' devoid of governing norms, where anonymous personalities ran C 2011 Musetta Durkee. t J.D. Candidate, 2012, University of California, Berkeley School of Law. 1. Lyrissa Barnett Lidsky, Anonymity in Cyberspace: What Can We LearnfromJohn Doe?, 50 B.C. L. REv. 1373, 1373-74 (2009). 2. As will be discussed below, there has been some conflation of two separate services that allow users to access the Internet, on the one hand, and engage in various activities, speech, and communication, on the other. Most basically, this Note distinguishes between Internet Service Providers (JSPs) and Online Service Providers (OSPs) in order to separate those services and companies involved with providing subscribers access to the infrastructure of the Internet (ISPs, and their subscribers) and those services and companies involved with providing users with online applications, services, platforms, and spaces on the Internet (OSPs and their users). -
Challenges in Web Search Engines
Challenges in Web Search Engines Monika R. Henzinger Rajeev Motwani* Craig Silverstein Google Inc. Department of Computer Science Google Inc. 2400 Bayshore Parkway Stanford University 2400 Bayshore Parkway Mountain View, CA 94043 Stanford, CA 94305 Mountain View, CA 94043 [email protected] [email protected] [email protected] Abstract or a combination thereof. There are web ranking optimiza• tion services which, for a fee, claim to place a given web site This article presents a high-level discussion of highly on a given search engine. some problems that are unique to web search en• Unfortunately, spamming has become so prevalent that ev• gines. The goal is to raise awareness and stimulate ery commercial search engine has had to take measures to research in these areas. identify and remove spam. Without such measures, the qual• ity of the rankings suffers severely. Traditional research in information retrieval has not had to 1 Introduction deal with this problem of "malicious" content in the corpora. Quite certainly, this problem is not present in the benchmark Web search engines are faced with a number of difficult prob• document collections used by researchers in the past; indeed, lems in maintaining or enhancing the quality of their perfor• those collections consist exclusively of high-quality content mance. These problems are either unique to this domain, or such as newspaper or scientific articles. Similarly, the spam novel variants of problems that have been studied in the liter• problem is not present in the context of intranets, the web that ature. Our goal in writing this article is to raise awareness of exists within a corporation. -
Social Media Why You Should Care What Is Social Media? Social Network
Social Media Why You Should Care IST 331 - Olivier Georgeon, Frank Ritter 31 oct 15 • eMarketer (2007) estimated by 2011 one-half Examples of all Internet users will use social networking • Facebook regulary. • YouTube • By 2015, 75% use • Myspace • Twitter • Del.icio.us • Digg • Etc… 2 What is Social Media? Social Network • Social Network • Online communities of people who share • User Generated Content (UGC) interests and activities, • Social Bookmarking • … or who are interested in exploring the interests and activities of others. • Examples: Facebook, MySpace, LinkedIn, Orkut • Falls to analysis with tools in Ch. 9 3 4 User Generated Content (UGC) Social Bookmarking • A method for Internet users to store, organize, search, • or Consumer Generated Media (CGM) and manage bookmarks of web pages on the Internet with the help of metadata. • Based on communities; • Defined: Media content that is publicly – The more people who bookmark a piece of content, the more available and produced by end-users (user). value it is determined to have. • Examples: Digg, Del.icio.us, StumbleUpon, and reddit….and now combinations • Usually supported by a social network • Examples: Blogs, Micro-blogs, YouTube video, Flickr photos, Wiki content, Facebook wall posts, reddit, Second Life… 5 6 Social Media Principles Generate an activity stream • Automatic • Who you are – Google History, Google Analytics – Personalization • Blog • Who you know • Micro-blog – Browse network – Twitter, yammer, identi.ca • What you do • Mailing groups – Generate an activity stream -
Objective Assessment of Cerebellar Ataxia: a Comprehensive and Refned Approach Bipasha Kashyap1 ✉ , Dung Phan1, Pubudu N
www.nature.com/scientificreports OPEN Objective Assessment of Cerebellar Ataxia: A Comprehensive and Refned Approach Bipasha Kashyap1 ✉ , Dung Phan1, Pubudu N. Pathirana1, Malcolm Horne2, Laura Power3 & David Szmulewicz2,3,4 Parametric analysis of Cerebellar Ataxia (CA) could be of immense value compared to its subjective clinical assessments. This study focuses on a comprehensive scheme for objective assessment of CA through the instrumented versions of 9 commonly used neurological tests in 5 domains- speech, upper limb, lower limb, gait and balance. Twenty-three individuals diagnosed with CA to varying degrees and eleven age-matched healthy controls were recruited. Wearable inertial sensors and Kinect camera were utilised for data acquisition. Binary and multilabel discrimination power and intra-domain relationships of the features extracted from the sensor measures and the clinical scores were compared using Graph Theory, Centrality Measures, Random Forest binary and multilabel classifcation approaches. An optimal subset of 13 most important Principal Component (PC) features were selected for CA- control classifcation. This classifcation model resulted in an impressive performance accuracy of 97% (F1 score = 95.2%) with Holmesian dimensions distributed as 47.7% Stability, 6.3% Timing, 38.75% Accuracy and 7.24% Rhythmicity. Another optimal subset of 11 PC features demonstrated an F1 score of 84.2% in mapping the total 27 PC across 5 domains during CA multilabel discrimination. In both cases, the balance (Romberg) test contributed the most (31.1% and 42% respectively), followed by the peripheral tests whereas gait (Walking) test contributed the least. These fndings paved the way for a better understanding of the feasibility of an instrumented system to assist informed clinical decision- making. -
Network Overlap and Content Sharing on Social Media Platforms
Network Overlap and Content Sharing on Social Media Platforms Jing Peng1, Ashish Agarwal2, Kartik Hosanagar3, Raghuram Iyengar3 1School of Business, University of Connecticut 2McCombs School of Business, University of Texas at Austin 3The Wharton School, University of Pennsylvania [email protected] [email protected] {kartikh, riyengar}@wharton.upenn.edu February 15, 2017 Acknowledgments. We benefited from feedback from session participants at 2013 Symposium on Statistical Challenges in eCommerce Research, 2014 International Conference on Information Systems, 2015 Workshop on Information in Networks, 2015 INFORMS Annual Meeting, and 2015 Workshop on Information Systems and Economics. The authors would like to thank Professors Christophe Van den Bulte, Paul Shaman, and Dylan Small for helpful discussions. This project was made possible by financial support extended to the first author through Mack Institute Research Fellowship, President Gutmann's Leadership Award, and Baker Retailing Center PhD Research Grant. 1 Network Overlap and Content Sharing on Social Media Platforms ABSTRACT We study the impact of network overlap – the overlap in network connections between two users – on content sharing in directed social media platforms. We propose a hazards model that flexibly captures the impact of three different measures of network overlap (i.e., common followees, common followers and common mutual followers) on content sharing. Our results indicate a receiver is more likely to share content from a sender with whom they share more common followees, common followers or common mutual followers after accounting for other measures. Additionally, the effect of common followers and common mutual followers is positive when the content is novel but decreases, and may even become negative, when many others in the network have already adopted it. -
The Fourth Paradigm
ABOUT THE FOURTH PARADIGM This book presents the first broad look at the rapidly emerging field of data- THE FOUR intensive science, with the goal of influencing the worldwide scientific and com- puting research communities and inspiring the next generation of scientists. Increasingly, scientific breakthroughs will be powered by advanced computing capabilities that help researchers manipulate and explore massive datasets. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another, and with technologists, in areas of eScience such as databases, workflow management, visualization, and cloud- computing technologies. This collection of essays expands on the vision of pio- T neering computer scientist Jim Gray for a new, fourth paradigm of discovery based H PARADIGM on data-intensive science and offers insights into how it can be fully realized. “The impact of Jim Gray’s thinking is continuing to get people to think in a new way about how data and software are redefining what it means to do science.” —Bill GaTES “I often tell people working in eScience that they aren’t in this field because they are visionaries or super-intelligent—it’s because they care about science The and they are alive now. It is about technology changing the world, and science taking advantage of it, to do more and do better.” —RhyS FRANCIS, AUSTRALIAN eRESEARCH INFRASTRUCTURE COUNCIL F OURTH “One of the greatest challenges for 21st-century science is how we respond to this new era of data-intensive -
Facebook Timeline
Facebook Timeline 2003 October • Mark Zuckerberg releases Facemash, the predecessor to Facebook. It was described as a Harvard University version of Hot or Not. 2004 January • Zuckerberg begins writing Facebook. • Zuckerberg registers thefacebook.com domain. February • Zuckerberg launches Facebook on February 4. 650 Harvard students joined thefacebook.com in the first week of launch. March • Facebook expands to MIT, Boston University, Boston College, Northeastern University, Stanford University, Dartmouth College, Columbia University, and Yale University. April • Zuckerberg, Dustin Moskovitz, and Eduardo Saverin form Thefacebook.com LLC, a partnership. June • Facebook receives its first investment from PayPal co-founder Peter Thiel for US$500,000. • Facebook incorporates into a new company, and Napster co-founder Sean Parker becomes its president. • Facebook moves its base of operations to Palo Alto, California. N. Lee, Facebook Nation, DOI: 10.1007/978-1-4614-5308-6, 211 Ó Springer Science+Business Media New York 2013 212 Facebook Timeline August • To compete with growing campus-only service i2hub, Zuckerberg launches Wirehog. It is a precursor to Facebook Platform applications. September • ConnectU files a lawsuit against Zuckerberg and other Facebook founders, resulting in a $65 million settlement. October • Maurice Werdegar of WTI Partner provides Facebook a $300,000 three-year credit line. December • Facebook achieves its one millionth registered user. 2005 February • Maurice Werdegar of WTI Partner provides Facebook a second $300,000 credit line and a $25,000 equity investment. April • Venture capital firm Accel Partners invests $12.7 million into Facebook. Accel’s partner and President Jim Breyer also puts up $1 million of his own money. -
Stanford University's Economic Impact Via Innovation and Entrepreneurship
Full text available at: http://dx.doi.org/10.1561/0300000074 Impact: Stanford University’s Economic Impact via Innovation and Entrepreneurship Charles E. Eesley Associate Professor in Management Science & Engineering W.M. Keck Foundation Faculty Scholar, School of Engineering Stanford University William F. Miller† Herbert Hoover Professor of Public and Private Management Emeritus Professor of Computer Science Emeritus and former Provost Stanford University and Faculty Co-director, SPRIE Boston — Delft Full text available at: http://dx.doi.org/10.1561/0300000074 Contents 1 Executive Summary2 1.1 Regional and Local Impact................. 3 1.2 Stanford’s Approach ..................... 4 1.3 Nonprofits and Social Innovation .............. 8 1.4 Alumni Founders and Leaders ................ 9 2 Creating an Entrepreneurial Ecosystem 12 2.1 History of Stanford and Silicon Valley ........... 12 3 Analyzing Stanford’s Entrepreneurial Footprint 17 3.1 Case Study: Google Inc., the Global Reach of One Stanford Startup ............................ 20 3.2 The Types of Companies Stanford Graduates Create .... 22 3.3 The BASES Study ...................... 30 4 Funding Startup Businesses 33 4.1 Study of Investors ...................... 38 4.2 Alumni Initiatives: Stanford Angels & Entrepreneurs Alumni Group ............................ 44 4.3 Case Example: Clint Korver ................. 44 5 How Stanford’s Academic Experience Creates Entrepreneurs 46 Full text available at: http://dx.doi.org/10.1561/0300000074 6 Changing Patterns in Entrepreneurial Career Paths 52 7 Social Innovation, Non-Profits, and Social Entrepreneurs 57 7.1 Case Example: Eric Krock .................. 58 7.2 Stanford Centers and Programs for Social Entrepreneurs . 59 7.3 Case Example: Miriam Rivera ................ 61 7.4 Creating Non-Profit Organizations ............. 63 8 The Lean Startup 68 9 How Stanford Supports Entrepreneurship—Programs, Cen- ters, Projects 77 9.1 Stanford Technology Ventures Program ......... -
SIGMOD Flyer
DATES: Research paper SIGMOD 2006 abstracts Nov. 15, 2005 Research papers, 25th ACM SIGMOD International Conference on demonstrations, Management of Data industrial talks, tutorials, panels Nov. 29, 2005 June 26- June 29, 2006 Author Notification Feb. 24, 2006 Chicago, USA The annual ACM SIGMOD conference is a leading international forum for database researchers, developers, and users to explore cutting-edge ideas and results, and to exchange techniques, tools, and experiences. We invite the submission of original research contributions as well as proposals for demonstrations, tutorials, industrial presentations, and panels. We encourage submissions relating to all aspects of data management defined broadly and particularly ORGANIZERS: encourage work that represent deep technical insights or present new abstractions and novel approaches to problems of significance. We especially welcome submissions that help identify and solve data management systems issues by General Chair leveraging knowledge of applications and related areas, such as information retrieval and search, operating systems & Clement Yu, U. of Illinois storage technologies, and web services. Areas of interest include but are not limited to: at Chicago • Benchmarking and performance evaluation Vice Gen. Chair • Data cleaning and integration Peter Scheuermann, Northwestern Univ. • Database monitoring and tuning PC Chair • Data privacy and security Surajit Chaudhuri, • Data warehousing and decision-support systems Microsoft Research • Embedded, sensor, mobile databases and applications Demo. Chair Anastassia Ailamaki, CMU • Managing uncertain and imprecise information Industrial PC Chair • Peer-to-peer data management Alon Halevy, U. of • Personalized information systems Washington, Seattle • Query processing and optimization Panels Chair Christian S. Jensen, • Replication, caching, and publish-subscribe systems Aalborg University • Text search and database querying Tutorials Chair • Semi-structured data David DeWitt, U. -
Abstract Counterexample-Based Refinement for Powerset
Abstract Counterexample-based Refinement for Powerset Domains R. Manevich1,†, J. Field2 , T. A. Henzinger3,§, G. Ramalingam4,¶, and M. Sagiv1 1 Tel Aviv University, {rumster,msagiv}@tau.ac.il 2 IBM T.J. Watson Research Center, [email protected] 3 EPFL, [email protected] 4 Microsoft Research India, [email protected] Abstract. Counterexample-guided abstraction refinement (CEGAR) is a powerful technique to scale automatic program analysis techniques to large programs. However, so far it has been used primarily for model checking in the context of predicate abstraction. We formalize CEGAR for general powerset domains. If a spurious abstract counterexample needs to be removed through abstraction refinement, there are often several choices, such as which program location(s) to refine, which ab- stract domain(s) to use at different locations, and which abstract values to compute. We define several plausible preference orderings on abstrac- tion refinements, such as refining as “late” as possible and as “coarse” as possible. We present generic algorithms for finding refinements that are optimal with respect to the different preference orderings. We also compare the different orderings with respect to desirable properties, in- cluding the property if locally optimal refinements compose to a global optimum. Finally, we point out some difficulties with CEGAR for non- powerset domains. 1 Introduction The CEGAR (Counterexample-guided Abstraction Refinement) paradigm [1, 3] has been the subject of a significant body of work in the automatic verification community. The basic idea is as follows. First, we statically analyze a program using a given abstraction. When an error is discovered, the analyzer generates an abstract counterexample, and checks whether the error occurs in the corre- sponding concrete execution path. -
Microhoo: Lessons from a Takeover Attempt Nihat Aktas, Eric De Bodt
MicroHoo: Lessons from a takeover attempt Nihat Aktas, Eric de Bodt, and Richard Roll This draft: July 14, 2010 ABSTRACT On February 1, 2008, Microsoft offered $43.7 billion for Yahoo. This was a milestone in the Microsoft versus Google battle to control the internet search industry and the related online advertising market. We provide an in-depth analysis of this failed takeover attempt. We attempt to identify the sources of overbidding (signaling, hubris-overconfidence, rational overpayment) and we show that the corporate control market has a disciplinary dimension but of an incidental and latent nature. Our results highlight the existence of takeover anticipation premiums in the stock prices of the potential targets. JEL classification: G34 Keywords: Overbidding; Competitive advantage; Rational overpayment; Latent competition Aktas de Bodt Roll Univ. Lille Nord de EMLYON Business UCLA Anderson France School 110 Westwood Plaza ECCCS Address 23 av. Guy de Collongue Los Angeles, CA 90095- 1 place Déliot - BP381 69130 Ecully 1481 59020 Lille Cédex France USA France Voice +33-4-7833-7847 +33-3-2090-7477 +1-310-825-6118 Fax +33-4-7833-7928 +33-3-2090-7629 +1-310-206-8404 E-mail [email protected] eric.debodt@univ- [email protected] lille2.fr 1 MicroHoo: Lessons from a takeover attempt 1. Introduction Fast Internet access, software as a service, cloud computing, netbooks, mobile platforms, one-line application stores,…, the first decade of the twenty-first century brought all the ingredients of a new technological revolution. These new technologies share one common denominator: the Internet. Two large competitors are face to face. -
A Case Study of the Reddit Community
An Exploration of Discussion Threads in Social News Sites: A Case Study of the Reddit Community Tim Weninger Xihao Avi Zhu Jiawei Han Department of Computer Science University of Illinois Urbana-Champaign Urbana, Illinois 61801 Email: fweninge1, zhu40, [email protected] Abstract—Social news and content aggregation Web sites have submission. These comment threads provide a user-generated become massive repositories of valuable knowledge on a diverse and user-curated commentary on the topic at hand. Unlike range of topics. Millions of Web-users are able to leverage these message board or Facebook-style comments that list comments platforms to submit, view and discuss nearly anything. The users in a flat, chronological order, or Twitter discussions that are themselves exclusively curate the content with an intricate system person-to-person and oftentimes difficult to discern, comment of submissions, voting and discussion. Furthermore, the data on threads in the social news paradigm are permanent (although social news Web sites is extremely well organized by its user-base, which opens the door for opportunities to leverage this data for editable), well-formed and hierarchical. The hierarchical nature other purposes just like Wikipedia data has been used for many of comment threads, where the discussion structure resembles other purposes. In this paper we study a popular social news a tree, is especially important because this allows divergent Web site called Reddit. Our investigation looks at the dynamics sub-topics resulting in a more robust overall discussion. of its discussion threads, and asks two main questions: (1) to In this paper we explore the social news site Reddit in order what extent do discussion threads resemble a topical hierarchy? and (2) Can discussion threads be used to enhance Web search? to gain a deeper understanding on the social, temporal, and We show interesting results for these questions on a very large topical methods that allow these types of user-powered Web snapshot several sub-communities of the Reddit Web site.