People? Motives and Uses of Facebook Adam N
Total Page:16
File Type:pdf, Size:1020Kb

Load more
Recommended publications
-
Metadata for Semantic and Social Applications
etadata is a key aspect of our evolving infrastructure for information management, social computing, and scientific collaboration. DC-2008M will focus on metadata challenges, solutions, and innovation in initiatives and activities underlying semantic and social applications. Metadata is part of the fabric of social computing, which includes the use of wikis, blogs, and tagging for collaboration and participation. Metadata also underlies the development of semantic applications, and the Semantic Web — the representation and integration of multimedia knowledge structures on the basis of semantic models. These two trends flow together in applications such as Wikipedia, where authors collectively create structured information that can be extracted and used to enhance access to and use of information sources. Recent discussion has focused on how existing bibliographic standards can be expressed as Semantic Metadata for Web vocabularies to facilitate the ingration of library and cultural heritage data with other types of data. Harnessing the efforts of content providers and end-users to link, tag, edit, and describe their Semantic and information in interoperable ways (”participatory metadata”) is a key step towards providing knowledge environments that are scalable, self-correcting, and evolvable. Social Applications DC-2008 will explore conceptual and practical issues in the development and deployment of semantic and social applications to meet the needs of specific communities of practice. Edited by Jane Greenberg and Wolfgang Klas DC-2008 -
A Study on Impact of Facebook on Teenagers
International Journal of Science and Research (IJSR) ISSN: 2319-7064 Impact Factor (2018): 7.426 A Study on Impact of Facebook on Teenagers S. T. Saravana Kumar1, S. B. Jenanee2 1Assistant Professor, Department of Commerce, Sri Krishna Adithya College of Arts & Science, Kovaipudur, Coimbatore – 42, India 2III B.Com (AF), Department of Commerce, Sri Krishna Adithya College of Arts & Science, Kovaipudur, Coimbatore – 42, India 1. Introduction still lack of strong empirical evidence to show how the use of these tools brings impact in teenager’s life. In the early 2000’s, the Web became much more personal as social networking websites were introduced and embraced 1.4 Methodology of the Study by the masses. Social networking sites (SNS) are defined as web-based services that allow individuals to construct a The methodology of this study includes the description and public or semi-public profile within a limited system, discussion of research design, sample size, sampling articulate a list of other users with whom they share a technique, tools and procedures of data collection and connection, and view and traverse their list of connections methods of analysis. The validity and value of a research and those made by others within the system. The nature and depends on the systematic method of collecting the data and terms of these connections may vary from site to site analyzing them insightfully and methodologically. In the present study, extensive and systematic use of primary data Here are some prominent examples of social media- along with the secondary data has been made. Facebook is a popular free social networking website that allows registered users to create profiles, upload photos Sources of Data and video, send messages and keep in touch with friends, Primary data family and colleagues. -
Aristotelian Rhetoric and Facebook Success in Israel's 2013 Election Campaign
Online Information Review Aristotelian rhetoric and Facebook success in Israel's 2013 election campaign: Tal Samuel-Azran Moran Yarchi Gadi Wolfsfeld Article information: To cite this document: Tal Samuel-Azran Moran Yarchi Gadi Wolfsfeld , (2015),"Aristotelian rhetoric and Facebook success in Israel's 2013 election campaign", Online Information Review, Vol. 39 Iss 2 pp. - Permanent link to this document: http://dx.doi.org/10.1108/OIR-11-2014-0279 Downloaded on: 30 March 2015, At: 00:49 (PT) References: this document contains references to 0 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 18 times since 2015* Users who downloaded this article also downloaded: G E Gorman, (2015),"What’s Missing in the Digital World? Access, Digital Literacy and Digital Citizenship", Online Information Review, Vol. 39 Iss 2 pp. - Noelia Sanchez-Casado, Juan Gabriel Cegarra-Navarro, Eva Tomaseti-Solano, (2015),"Linking social networks to Utilitarian benefits through counter-knowledge", Online Information Review, Vol. 39 Iss 2 pp. - Azi Lev-On, (2015),"Uses and gratifications of members of communities of practice", Online Information Review, Vol. 39 Iss 2 pp. - Access to this document was granted through an Emerald subscription provided by 172715 [] For Authors If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.com Emerald is a global publisher linking research and practice to the benefit of society. -
A Comparison of Information Seeking Using Search Engines and Social Networks
A Comparison of Information Seeking Using Search Engines and Social Networks Meredith Ringel Morris1, Jaime Teevan1, Katrina Panovich2 1Microsoft Research, Redmond, WA, USA, 2Massachusetts Institute of Technology, Cambridge, MA, USA {merrie, teevan}@microsoft.com, [email protected] Abstract et al. 2009 or Groupization by Morris et al. 2008). Social The Web has become an important information repository; search engines can also be devised using the output of so- often it is the first source a person turns to with an informa- cial tagging systems such as delicious (delicious.com). tion need. One common way to search the Web is with a Social search also encompasses active requests for help search engine. However, it is not always easy for people to from the searcher to other people. Evans and Chi (2008) find what they are looking for with keyword search, and at describe the stages of the search process when people tend times the desired information may not be readily available to interact with others. Morris et al. (2010) surveyed Face- online. An alternative, facilitated by the rise of social media, is to pose a question to one‟s online social network. In this book and Twitter users about situations in which they used paper, we explore the pros and cons of using a social net- a status message to ask questions of their social networks. working tool to fill an information need, as compared with a A well-studied type of social searching behavior is the search engine. We describe a study in which 12 participants posting of a question to a Q&A site (e.g., Harper et al. -
The Effect of Social Media Language on EFL Learners' Academic Writing
PEOPLE’S DEMOCRATIC REPUBLIC OF ALGERIA MINISTRY OF HIGHER EDUCATION AND SCIENTIFIC RESEARCH UNIVERSITY OF MOHAMED BOUDIAF - M’SILA FACULTY OF LETTERS AND LANGUAGES DOMAIN: FOREIGN LANGUAGES DEPARTMENT OF ENGLISH STREAM: ENGLISH LANGUAGE N°:……………………………………….. OPTION: LINGUISTICS The Effect of Social Media Language on EFL Learners’ Academic Writing Performance. Case of Master One Linguistics Students at M’sila University. Dissertation Submitted to the Department of English in Partial Fulfillment of the Requirements for the Degree of Master Candidates Supervised by Miss. Nedjla BENSAID Dr. Mourad TOUATI Miss. Fatima Zohra MOUMEN Board of Examiners Mr. Saber Mouhamed Boudiaf University, Chairperson M’sila Dr. Touati Mourad Mouhamed Boudiaf University, Supervisor M’sila Ms. Hamouma Mouhamed Boudiaf University, Examiner M’sila June 2019 DEDICATION This thesis is dedicated to: My precious beloved parents who have always been a constant source of support and encouragement during the challenges of my whole college life, and for their endless care and love. My treasured brothers and sister: Issam, Anis & Amani, and to my nephew Aylane, whom I am truly grateful for having in my life. My dear family, teachers, colleagues and friends. All people who left a touch in my life. BENSAID Nedjla II DEDICATION To my dear parents who gave me strength and confidence and have been the source of inspiration behind all my achievements. To my husband and my lovely brothers for their support and love. To all my family and friends for their encouragement and prayers . I appreciate you all . To everyone who stood beside me and had contributed to my education. MOUMEN Fatima Zohra III Acknowledgments We would like to express our deeper and sincere gratitude to our respected supervisor Dr. -
A Federated Search and Social Recommendation Widget
A Federated Search and Social Recommendation Widget Sten Govaerts1 Sandy El Helou2 Erik Duval3 Denis Gillet4 Dept. Computer Science1,3 REACT group2,4 Katholieke Universiteit Leuven Ecole Polytechnique Fed´ erale´ de Lausanne Celestijnenlaan 200A, Heverlee, Belgium 1015 Lausanne, Switzerland fsten.govaerts1, [email protected] fsandy.elhelou2, denis.gillet4g@epfl.ch ABSTRACT are very useful, but their generality can sometimes be an ob- This paper presents a federated search and social recommen- stacle and this can make it difficult to know where to search dation widget. It describes the widget’s interface and the un- for the needed information [2]. Federated searching over derlying social recommendation engine. A preliminary eval- collections of topic-specific repositories can assist with this uation of the widget’s usability and usefulness involving 15 and save time. When the user sends a search request, the subjects is also discussed. The evaluation helped identify us- federated search widget collects relevant resources from dif- ability problems that will be addressed prior to the widget’s ferent social media sites [3], repositories and search engines. usage in a real learning context. Before rendering aggregated results, the widget calls a per- sonalized social recommendation service deemed as crucial Author Keywords in helping users select relevant resources especially in our federated search, social recommendations, widget, Web, per- information overload age [4,5]. The recommendation ser- sonal learning environment (PLE), Pagerank, social media, vice ranks these resources according to their global popu- Web 2.0 larity and most importantly their popularity within the social network of the target user. Ranks are computed by exploiting attention metadata and social networks in the widget. -
Unicorn: a System for Searching the Social Graph
Unicorn: A System for Searching the Social Graph Michael Curtiss, Iain Becker, Tudor Bosman, Sergey Doroshenko, Lucian Grijincu, Tom Jackson, Sandhya Kunnatur, Soren Lassen, Philip Pronin, Sriram Sankar, Guanghao Shen, Gintaras Woss, Chao Yang, Ning Zhang Facebook, Inc. ABSTRACT rative of the evolution of Unicorn's architecture, as well as Unicorn is an online, in-memory social graph-aware index- documentation for the major features and components of ing system designed to search trillions of edges between tens the system. of billions of users and entities on thousands of commodity To the best of our knowledge, no other online graph re- servers. Unicorn is based on standard concepts in informa- trieval system has ever been built with the scale of Unicorn tion retrieval, but it includes features to promote results in terms of both data volume and query volume. The sys- with good social proximity. It also supports queries that re- tem serves tens of billions of nodes and trillions of edges quire multiple round-trips to leaves in order to retrieve ob- at scale while accounting for per-edge privacy, and it must jects that are more than one edge away from source nodes. also support realtime updates for all edges and nodes while Unicorn is designed to answer billions of queries per day at serving billions of daily queries at low latencies. latencies in the hundreds of milliseconds, and it serves as an This paper includes three main contributions: infrastructural building block for Facebook's Graph Search • We describe how we applied common information re- product. In this paper, we describe the data model and trieval architectural concepts to the domain of the so- query language supported by Unicorn. -
The Top 10 Alternative Search Engines (ASE) - Within Selected Categories Ranked by Webometric Indicators
The Top 10 Alternative search Engines (ASE) - within Selected Categories Ranked by Webometric Indicators Bernd Markscheff el Bastian Eine Within the scientifi c fi eld of webometrics many research objects had been analyzed and compared with the help of webometric indicators (e.g., the performance of a whole country, a research group or an indi- vidual). This paper presents a ranking of ASEs which is based on webo- metric indicators. As search engines have become an essential tool for searching for information on the web many alternative search services have specialized in fi nding topic- or format-specifi c search results. By creating a ranking of these ASEs within selected categories we present an overview of the ASEs which are currently available. Through webo- metric indicators the ASEs were compared and the most popular ASEs of the respective categories determined. Keywords: Search engines, Webometric indicators Bernd Markscheff el Chair of Information and 1. Introduction Knowledge Management Technische Universität While searching for information on the web, search en- Ilmenau gines can assist the user to fi nd satisfying results. Although, P.O. Box 100565 just a few dominate the search engine market a large num- 98684 Ilmenau ber of diff erent web search services and tools exist (Maaβ Germany et al., [1]). Beside the well known universal search engines bernd.markscheff el@ like Google, Yahoo and Bing several ASEs are specialized tuilmenau.de in providing options to search for special document types, specifi c topics or time-sensitive information (Gelernter [2]; Bastian Eine Consultant for Search Engine Originally presented at the 7th International Conference on Webometrics, Optimization and Online Informetrics and Scientometrics (WIS) and 12th COLLNET Meeting, Marketing September 20–23, 2011, Istanbul Bilgi University, Istanbul, Turkey. -
Searching the Enterprise
R Foundations and Trends• in Information Retrieval Vol. 11, No. 1 (2017) 1–142 c 2017 U. Kruschwitz and C. Hull • DOI: 10.1561/1500000053 Searching the Enterprise Udo Kruschwitz Charlie Hull University of Essex, UK Flax, UK [email protected] charlie@flax.co.uk Contents 1 Introduction 2 1.1 Overview........................... 3 1.2 Examples........................... 5 1.3 PerceptionandReality . 9 1.4 RecentDevelopments . 10 1.5 Outline............................ 11 2 Plotting the Landscape 13 2.1 The Changing Face of Search . 13 2.2 DefiningEnterpriseSearch . 14 2.3 Related Search Areas and Applications . 17 2.4 SearchTechniques. 34 2.5 Contextualisation ...................... 37 2.6 ConcludingRemarks. 49 3 Enterprise Search Basics 52 3.1 StructureofData ...................... 53 3.2 CollectionGathering. 59 3.3 SearchArchitectures. 63 3.4 Information Needs and Applications . 68 3.5 SearchContext ....................... 76 ii iii 3.6 UserModelling........................ 78 3.7 Tools, Frameworks and Resources . 81 4 Evaluation 82 4.1 RelevanceandMetrics. 83 4.2 Evaluation Paradigms and Campaigns . 85 4.3 TestCollections ....................... 89 4.4 LessonsLearned ....................... 94 5 Making Enterprise Search Work 95 5.1 PuttingtheUserinControl . 96 5.2 Relevance Tuning and Support . 103 6 The Future 110 6.1 GeneralTrends........................ 110 6.2 TechnicalDevelopments. 111 6.3 Moving towards Cooperative Search . 113 6.4 SomeResearchChallenges . 114 6.5 FinalWords ......................... 117 7 Conclusion 118 Acknowledgements 120 References 121 Abstract Search has become ubiquitous but that does not mean that search has been solved. Enterprise search, which is broadly speaking the use of information retrieval technology to find information within organisa- tions, is a good example to illustrate this. -
Collaborative Information Access: a Conversational Search Approach
ICCBR Workshop on Reasoning from Experiences on the Web (WebCBR-09), Seattle Collaborative Information Access: A Conversational Search Approach Saurav Sahay, Anushree Venkatesh, and Ashwin Ram College of Computing Georgia Institute of Technology Atlanta, GA Abstract. Knowledge and user generated content is proliferating on the web in scientific publications, information portals and online social me- dia. This knowledge explosion has continued to outpace technological innovation in efficient information access technologies. In this paper, we describe the methods and technologies for ‘Conversational Search’ as an innovative solution to facilitate easier information access and reduce the information overload for users. Conversational Search is an interactive and collaborative information finding interaction. The participants in this interaction engage in social conversations aided with an intelligent information agent (Cobot) that provides contextually relevant search recommendations. The collaborative and conversational search activity helps users make faster and more informed search and discovery. It also helps the agent learn about conversations with interactions and social feedback to make better recommendations. Conversational search lever- agesthe social discovery process by integrating web information retrieval along with the social interactions. 1 Introduction Socially enabled online information search (social search) is a new phenomenon facilitated by recent Web technologies. This collaborative social search involves finding specific people in your network who have the knowledge you’re look- ing for or finding relevant information based on one’s social network. Social psychologists have experimentally validated that the act of social discussions have facilitated cognitive performance[1]. People in social groups can provide solutions (answers to questions)[2], pointers to databases or other people (meta- knowledge)[2][3] , validation and legitimation of ideas[2][4], can serve as mem- ory aids[5] and help with problem reformulation[2]. -
Natural Search User Interfaces
Natural Search User Interfaces Prof. Marti Hearst UC Berkeley March/April , 2012 Book full text freely available at: http://searchuserinterfaces.com What works well in search now? Faceted Navigation 3 Real-Time Suggestions http://netflix.com http://www.imamuseum.org/ 4 Forecasting the Future First: What are the larger trends? In technology? In society? Next: Project out from these. Preferences for Preferences for Preferences for Audio / Video / Touch Social Interaction Natural Language “Natural” Interfaces Statistical Analysis of Wide adoption of social Enormous Collections Advances in media & user-generated UI Design Of Behavioral and Other Data content 6 Trend: More Natural Queries Trend: Longer, more natural queries § The research suggests people prefer to state their information need rather than use keywords. § But after first using a search engine they quickly learned that full questions resulted in failure. 8 Trend: Longer, more natural queries § The research suggests people prefer to state their information need rather than use keywords. § But after first using a search engine they quickly learned that full questions resulted in failure. § Average query length continues to increase § In 2010 vs 2009, searches of 5-8 words were up 10%, while 1-2 word searches were down. 9 Trend: Longer, more natural queries § Social Question Answering Sites: § Information worded as questions increasing available § with the questions that the audience really wants the answers to, and § written in the language the audience wants to use. § AND with -
1 Public Records Resources Online
Public Records Resources Online How to Find Everything There Is to Know About "Mr./Ms. X" *Please see disclaimer at end of document* Summary of public records on Mr. / Ms. X . Starting with one or more Background Reports from the sources below can help provide an overview of where the person has lived and worked, as well as other pertinent information for searching, such as middle name or initial. They might also contain adverse filings and licensing information that you can later verify in other sources. Examples of vendors that provide background reports (for a fee): Westlaw/CLEAR (Thomson Reuters) $ Lexis/Accurint $ TLO $ His/her social security number is . These tools can help verify if an SSN is valid and related to a living person. SSN Validator Selective Service Online Verification He/she was born / died / naturalized . In addition to the Summary Reports in the first section of this guide, official death records may be found in resources on the federal, state, and local levels. The Genealogy Resources section of this guide might have other helpful resources for death records. Social Security Death Records The official federal record is the Social Security Death Index (SSDI). Only the subscription databases, such as Lexis, Westlaw, and TLO (all $) will have the most recent SSDI records, due to privacy restrictions. Try variations of spellings, or using only the last name and birth or death year and location if you're not finding an SSDI record. Ancestry Library $ Genealogy Bank SSDI Research Guide SSDI Databases Online State and Local Death, Burial, and Cemetery Records State and local death records will often provide more detailed information than an SSDI record, but they are not as easy to find.