Seamless Interoperability and Data Portability in the Social Web for Facilitating an Open and Heterogeneous Online Social Network Federation
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Social Media Tool Analysis
Social Media Tool Analysis John Saxon TCO 691 10 JUNE 2013 1. Orkut Introduction Orkut is a social networking website that allows a user to maintain existing relationships, while also providing a platform to form new relationships. The site is open to anyone over the age of 13, with no obvious bent toward one group, but is primarily used in Brazil and India, and dominated by the 18-25 demographic. Users can set up a profile, add friends, post status updates, share pictures and video, and comment on their friend’s profiles in “scraps.” Seven Building Blocks • Identity – Users of Orkut start by establishing a user profile, which is used to identify themselves to other users. • Conversations – Orkut users can start conversations with each other in a number of way, including an integrated instant messaging functionality and through “scraps,” which allows users to post on each other’s “scrapbooks” – pages tied to the user profile. • Sharing – Users can share pictures, videos, and status updates with other users, who can share feedback through commenting and/or “liking” a user’s post. • Presence – Presence on Orkut is limited to time-stamping of posts, providing other users an idea of how frequently a user is posting. • Relationships – Orkut’s main emphasis is on relationships, allowing users to friend each other as well as providing a number of methods for communication between users. • Reputation – Reputation on Orkut is limited to tracking the number of friends a user has, providing other users an idea of how connected that user is. • Groups – Users of Orkut can form “communities” where they can discuss and comment on shared interests with other users. -
ADL Report to Global Forum on Cyberhate 2015
Report of the Anti-Defamation League on Confronting Cyberhate 5th Global Forum for Combating Anti-Semitism May, 2015 ANTI-DEFAMATION LEAGUE Barry Curtiss-Lusher National Chair Abraham H. Foxman National Director Kenneth Jacobson Deputy National Director Milton S. Schneider President, Anti-Defamation League Foundation CIVIL RIGHTS DIVISION Christopher Wolf Chair Deborah M. Lauter Director Steven M. Freeman Associate Director Eva Vega-Olds Assistant Director Jonathan Vick Assistant Director, Cyberhate Response CENTER ON EXTREMISM Mitch Markow Chair Oren Segal Director Lauren Steinberg Terrorism Analyst For additional and updated resources please see: www.adl.org Copies of this publication are available in the Rita and Leo Greenland Library and Research Center. ©2015 Anti-Defamation League | Printed in the United States of America | All Rights Reserved Anti-Defamation League 605 Third Avenue, New York, NY 10158-3560 www.adl.org Table of Contents PREFACE .........................................................................................................................................................4 INTRODUCTION ..............................................................................................................................................5 CHARTING PROGRESS ....................................................................................................................................6 A NEW CHALLENGE: TERRORIST USE OF SOCIAL MEDIA ............................................................................11 RECOMMENDATIONS -
Native American Context Statement and Reconnaissance Level Survey Supplement
NATIVE AMERICAN CONTEXT STATEMENT AND RECONNAISSANCE LEVEL SURVEY SUPPLEMENT Prepared for The City of Minneapolis Department of Community Planning & Economic Development Prepared by Two Pines Resource Group, LLC FINAL July 2016 Cover Image Indian Tepees on the Site of Bridge Square with the John H. Stevens House, 1852 Collections of the Minnesota Historical Society (Neg. No. 583) Minneapolis Pow Wow, 1951 Collections of the Minnesota Historical Society (Neg. No. 35609) Minneapolis American Indian Center 1530 E Franklin Avenue NATIVE AMERICAN CONTEXT STATEMENT AND RECONNAISSANCE LEVEL SURVEY SUPPLEMENT Prepared for City of Minneapolis Department of Community Planning and Economic Development 250 South 4th Street Room 300, Public Service Center Minneapolis, MN 55415 Prepared by Eva B. Terrell, M.A. and Michelle M. Terrell, Ph.D., RPA Two Pines Resource Group, LLC 17711 260th Street Shafer, MN 55074 FINAL July 2016 MINNEAPOLIS NATIVE AMERICAN CONTEXT STATEMENT AND RECONNAISSANCE LEVEL SURVEY SUPPLEMENT This project is funded by the City of Minneapolis and with Federal funds from the National Park Service, U.S. Department of the Interior. The contents and opinions do not necessarily reflect the views or policies of the Department of the Interior, nor does the mention of trade names or commercial products constitute endorsement or recommendation by the Department of the Interior. This program receives Federal financial assistance for identification and protection of historic properties. Under Title VI of the Civil Rights Act of 1964 and Section 504 of the Rehabilitation Act of 1973, the U.S. Department of the Interior prohibits discrimination on the basis of race, color, national origin, or disability in its federally assisted programs. -
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 -
Los Angeles Lawyer June 2010 June2010 Issuemaster.Qxp 5/13/10 12:26 PM Page 5
June2010_IssueMaster.qxp 5/13/10 12:25 PM Page c1 2010 Lawyer-to-Lawyer Referral Guide June 2010 /$4 EARN MCLE CREDIT PLUS Protecting Divorce Web Site Look and Estate and Feel Planning page 40 page 34 Limitations of Privacy Rights page 12 Revoking Family Trusts page 16 The Lilly Ledbetter Fair Pay Act Strength of page 21 Character Los Angeles lawyers Michael D. Schwartz and Phillip R. Maltin explain the effective use of character evidence in civil trials page 26 June2010_IssueMaster.qxp 5/13/10 12:42 PM Page c2 Every Legal Issue. One Legal Source. June2010_IssueMaster.qxp 5/13/10 12:25 PM Page 1 Interim Dean Scott Howe and former Dean John Eastman at the Top 100 celebration. CHAPMAN UNIVERSITY SCHOOL OF LAW PROUDLY ANNOUNCES OUR RANKING AMONG THE TOP 100 OF ONE UNIVERSITY DRIVE, ORANGE, CA 92866 www.chapman.edu/law June2010_IssueMaster.qxp 5/13/10 12:25 PM Page 2 0/&'*3. ."/:40-65*0/4 Foepstfe!Qspufdujpo Q -"8'*3.$-*&/54 Q"$$&445007&3130'&44*0/"- -*"#*-*5:1307*%&34 Q0/-*/&"11-*$"5*0/4'03 &"4:$0.1-&5*0/ &/%034&%130'&44*0/"--*"#*-*5:*/463"/$,&3 Call 1-800-282-9786 today to speak to a specialist. 5 ' -*$&/4&$ 4"/%*&(003"/(&$06/5:-04"/(&-&44"/'3"/$*4$0 888")&3/*/463"/$&$0. June2010_IssueMaster.qxp 5/13/10 12:26 PM Page 3 FEATURES 26 Strength of Character BY MICHAEL D. SCHWARTZ AND PHILLIP R. MALTIN Stringent rules for the admission of character evidence in civil trials are designed to prevent jurors from deciding a case on the basis of which party is more likeable 34 Parting of the Ways BY HOWARD S. -
The Impact of Data Access Regimes on Artificial Intelligence and Machine Learning
A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Martens, Bertin Working Paper The impact of data access regimes on artificial intelligence and machine learning JRC Digital Economy Working Paper, No. 2018-09 Provided in Cooperation with: Joint Research Centre (JRC), European Commission Suggested Citation: Martens, Bertin (2018) : The impact of data access regimes on artificial intelligence and machine learning, JRC Digital Economy Working Paper, No. 2018-09, European Commission, Joint Research Centre (JRC), Seville This Version is available at: http://hdl.handle.net/10419/202237 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially Creative Commons Licences), you genannten Lizenz gewährten Nutzungsrechte. may exercise further usage rights as specified in the indicated licence. www.econstor.eu JRC Digital Economy Working Paper 2018-09 The impact of data access regimes on artificial intelligence and machine learning Bertin Martens December 2018 This publication is a Working Paper by the Joint Research Centre, the European Commission’s in-house science service. -
Bibliography of Erik Wilde
dretbiblio dretbiblio Erik Wilde's Bibliography References [1] AFIPS Fall Joint Computer Conference, San Francisco, California, December 1968. [2] Seventeenth IEEE Conference on Computer Communication Networks, Washington, D.C., 1978. [3] ACM SIGACT-SIGMOD Symposium on Principles of Database Systems, Los Angeles, Cal- ifornia, March 1982. ACM Press. [4] First Conference on Computer-Supported Cooperative Work, 1986. [5] 1987 ACM Conference on Hypertext, Chapel Hill, North Carolina, November 1987. ACM Press. [6] 18th IEEE International Symposium on Fault-Tolerant Computing, Tokyo, Japan, 1988. IEEE Computer Society Press. [7] Conference on Computer-Supported Cooperative Work, Portland, Oregon, 1988. ACM Press. [8] Conference on Office Information Systems, Palo Alto, California, March 1988. [9] 1989 ACM Conference on Hypertext, Pittsburgh, Pennsylvania, November 1989. ACM Press. [10] UNIX | The Legend Evolves. Summer 1990 UKUUG Conference, Buntingford, UK, 1990. UKUUG. [11] Fourth ACM Symposium on User Interface Software and Technology, Hilton Head, South Carolina, November 1991. [12] GLOBECOM'91 Conference, Phoenix, Arizona, 1991. IEEE Computer Society Press. [13] IEEE INFOCOM '91 Conference on Computer Communications, Bal Harbour, Florida, 1991. IEEE Computer Society Press. [14] IEEE International Conference on Communications, Denver, Colorado, June 1991. [15] International Workshop on CSCW, Berlin, Germany, April 1991. [16] Third ACM Conference on Hypertext, San Antonio, Texas, December 1991. ACM Press. [17] 11th Symposium on Reliable Distributed Systems, Houston, Texas, 1992. IEEE Computer Society Press. [18] 3rd Joint European Networking Conference, Innsbruck, Austria, May 1992. [19] Fourth ACM Conference on Hypertext, Milano, Italy, November 1992. ACM Press. [20] GLOBECOM'92 Conference, Orlando, Florida, December 1992. IEEE Computer Society Press. http://github.com/dret/biblio (August 29, 2018) 1 dretbiblio [21] IEEE INFOCOM '92 Conference on Computer Communications, Florence, Italy, 1992. -
North Korea Purloins Russian Technology to Add Teeth to Its Military Caliber
NEW DELHI TIMES R.N.I. No 53449/91 DL-SW-01/4124/17-19 (Monday/Tuesday same week) (Published Every Monday) New Delhi Page 16 Rs. 7.00 22 - 28 July 2019 Vol - 29 No. 25 Email : [email protected] Founder : Dr. Govind Narain Srivastava ISSN -2349-1221 Modi irradiates Christian victims of loopholed Defence Muslim oppression Procurement rot in Thailand With the world at large progressing with positive The country code of 66 on the incoming call speed and the concept of globalization seeing was unfamiliar, as was the number. its frutation with the spread of co-operative Usually I ignore such calls as they invariably and collaborative networks worldwide; among are threats from the worldwide network of the civic, economic and political spheres, the my fans or duct-cleaning companies worried defence sector of any nation in the modern about the air I breathe. But on that day, I took era becomes the top-priority... a chance. The other option... By Dr. Ankit Srivastava Page 3 By Tarek Fatah Page 2 North Korea purloins Russian technology to add teeth to its Military Caliber By NDT Special Bureau Page 2 Babies growing up with animals, Belief aids to climb the ladder Iran and its prospects for build stronger immune system of Success Democracy I meet so many mothers who won’t let their children walk All of us are on a daily struggle to be successful so as to be More than 80 million Iranians at home or living across the barefoot in the house or the park, won’t let them touch able to establish ourselves in society. -
Auswertung Onlinebefragung Social Media
HSD Auswertung Onlinebefragung Social Media Impressum Herausgeber Dezernat Kommunikation & Marketing Redaktion Rebecca Juwick M.A. Dezernat Kommunikation & Marketing Stand Februar 2016 2 Inhalt 1 Einleitung 4 2 Methode 5 3 Ergebnisse 6 Nutzung Social Networks 9 Zielgruppen 15 Funktionen & Inhalte 16 4 Fazit 22 3 Auswertung Social- Media-Umfrage 1 Einleitung Im Rahmen der Social-Media-Projektgruppe sollten die Anforderungen der unterschiedlichen Ziel- gruppen an das Social-Media-Angebot der Hochschule erhoben werden. Um dies möglichst effektiv umsetzen zu können, wurde eine Onlinebefragung für Studierende und Beschäftigte der Hochschule Düsseldorf durchgeführt. Diese liefen in zeitlichem Abstand zueinander jeweils 4 Wochen lang. Im Folgenden wird zuerst das methodische Vorgehen zur Befragung kurz erläutert, bevor die Ergeb- nisse vorgestellt werden. Alle Ergebnisse können den Datei-Anhängen „Auswertung_Studie- rende.xlsx“ und „Auswertung_Beschäftigte.xlsx“ entnommen werden. 4 Auswertung Social-Media-Umfrage 2 Methode Damit möglichst viele Studierende aus allen Fachbereichen und die Beschäftigten der Hochschule, unabhängig vom Standort, an der Erhebung teilnehmen konnten, wurde die Befragung als reine On- linebefragung durchgeführt. Aufgrund der Ähnlichkeit in Bezug auf die avisierten Zielgruppen, sowie der inhaltlichen Fragestellung wurde die Befragung in Kooperation mit der Campus IT, dem Daten- schutzbeauftragten und dem Fachbereich Sozial- und Kulturwissenschaften realisiert. Der Fragebogen wurde mithilfe der Software Unipark umgesetzt und über den entsprechenden Uni- park-Server für mehrere Wochen zur Beantwortung verfügbar gehalten. Der Umfang des Fragebo- gens wurde dabei so gewählt, dass eine Bearbeitungsdauer von 10 bis 15 Minuten – inklusive Brie- fing und Debriefing – nicht überschritten wurde. Zur Gewinnung von Teilnehmenden wurden diese über diverse Kanäle angesprochen. Auf der Start- seite des Internetauftritts der HSD wurde beispielsweise eine Meldung von der Pressestelle einge- stellt. -
Hard-Coded Censorship in Open Source Mastodon Clients — How Free Is Open Source?
Proceedings of the Conference on Technology Ethics 2020 - Tethics 2020 Hard-coded censorship in Open Source Mastodon clients — How Free is Open Source? Long paper Juhani Naskali 0000-0002-7559-2595 Information Systems Science, Turku School of Economics, University of Turku Turku, Finland juhani.naskali@utu.fi Abstract. This article analyses hard-coded domain blocking in open source soft- ware, using the GPL3-licensed Mastodon client Tusky as a case example. First, the question of whether such action is censorship is analysed. Second, the licensing compliance of such action is examined using the applicable open-source software and distribution licenses. Domain blocking is found to be censorship in the literal definition of the word, as well as possibly against some the used Google distribu- tion licenses — though some ambiguity remains, which calls for clarifications in the agreement terms. GPL allows for functionalities that limit the use of the software, as long as end-users are free to edit the source code and use a version of the appli- cation without such limitations. Such software is still open source, but no longer free (as in freedom). A multi-disciplinary ethical examination of domain blocking will be needed to ascertain whether such censorship is ethical, as all censorship is not necessarily wrong. Keywords: open source, FOSS, censorship, domain blocking, licensing terms 1 Introduction New technologies constantly create new challenges. Old laws and policies cannot al- ways predict future possibilities, and sometimes need to be re-examined. Open source software is a licensing method to freely distribute software code, but also an ideology of openness and inclusiveness, especially when it comes to FOSS (Free and Open-source software). -
Data Portability and Privacy
SEPTEMBER 2019 CHARTING A WAY FORWARD Data Portability and Privacy Erin Egan VICE PRESIDENT AND CHIEF PRIVACY OFFICER, POLICY CHARTING A WAY FORWARD 1 Table of Contents 03 I. Intro 06 II. The Challenge 09 III. Five Questions About Portability and Responsibility 09 QUESTION 1 What is “data portability”? 13 QUESTION 2 Which data should be portable? 14 QUESTION 3 Whose data should be portable? 15 QUESTION 4 How should we protect privacy while enabling portability? 20 QUESTION 5 After people’s data is transferred, who is responsible if the data is misused or otherwise improperly protected? 24 IV. What’s Next? 25 End Notes CHARTING A WAY FORWARD 2 Data Portability and Privacy 01 There’s growing agreement among policymakers around the world that data portability—the principle that you should be able to take the data you share with one service and move it to another—can help promote competition online and encourage the emergence of new services. Competition and data protection experts agree that, although there are complicated issues involved, portability helps people control their data and can make it easier for them to choose among online service providers. The benefits of data portability to people and markets are clear, which is why our CEO, Mark Zuckerberg, recently called for laws that guarantee portability.1 But to build portability tools people can trust and use effectively, we should develop clear rules about what kinds of data should be portable and who is responsible for protecting that data as it moves to different providers.2 The purpose of this paper is to advance the conversation about what those rules should be. -
Mastodon.Py Documentation Release 1.5.1
Mastodon.py Documentation Release 1.5.1 Lorenz Diener Mar 14, 2020 Contents 1 A note about rate limits 3 2 A note about pagination 5 3 Two notes about IDs 7 3.1 ID unpacking...............................................7 4 Error handling 9 5 A brief note on block lists 11 6 Return values 13 6.1 User dicts................................................. 13 6.2 Toot dicts................................................. 14 6.3 Mention dicts............................................... 15 6.4 Scheduled toot dicts........................................... 15 6.5 Poll dicts................................................. 16 6.6 Conversation dicts............................................ 16 6.7 Hashtag dicts............................................... 16 6.8 Hashtag usage history dicts....................................... 17 6.9 Emoji dicts................................................ 17 6.10 Application dicts............................................. 17 6.11 Relationship dicts............................................ 17 6.12 Filter dicts................................................ 18 6.13 Notification dicts............................................. 18 6.14 Context dicts............................................... 18 6.15 List dicts................................................. 19 6.16 Media dicts................................................ 19 6.17 Card dicts................................................. 20 6.18 Search result dicts............................................ 20 6.19 Instance dicts..............................................