Social scope: Enabling Information Discovery On Social Content Sites Presenters: Sahar Delroshan Rezan Amiri Azad university of Kurdistan

outline Overview Of Social Scope Case Study With Yahoo! Travel Motivating Example Social Scope Platform Layers of social Scope Data and query Model of Social Content Management Conclusion Azad university of Kurdistan

Overview Of Social Scope Recently, many content sites have started encouraging their users to engage in social activities such as adding buddies on Yahoo! Travel and sharing articles with their friends on New York Times.This has led to the emergence of social content sites,which is being facilitated by initiatives like Open ID and Open Social. Azad university of Kurdistan

Content Site Are Popular Azad university of Kurdistan

Social Sites Are Popular! Azad university of Kurdistan

Social Content Sites Azad university of Kurdistan

Case Study With Yahoo ! Travel Y!Travel is a typical content site that is gradually evolving into a social content site. Y! travel Data: Y ! Travel maintains a comprehensive set of travel objectes : cities , restaurants, etc. Y! Travel Queries: Users interact with Y!Travel through a search interface, where they enter a set of keywords and obtain a list of travel objects considered relevant to their queries Azad university of Kurdistan

Case Study With Yahoo ! Travel we detect location terms in queries and classify each query into three classes: general, categorical, and specific.4 General queries are those containing terms like “things to do”, “attraction”, or just a location by itself. Over 50% of the queries fall into this class, and about 60% of those queries contain a location. Categorical queries refer to those containing terms like “hotel”, “family”, “historic”, etc. About 30% of the queries fall into this class and a majority of them mention a location. Finally, there are also about 8% of the queries looking for specific destinations like “Disneyland” and “Yosemite Park”. Azad university of Kurdistan

Motivation Example Example : Two major paradigms : Search for “Denver attractions” Two major paradigms : 1-semantic relevance 2- social relevance EXAMPLE 1. John is in Denver for a conference. Having one day free, he visits Y!Travel and searches for “Denver attractions”. John has in the past visited quite a few baseball fields on Y!Travel and has many friends on Facebook with interests in “baseball”. With this knowledge, Y!Travel recommends to him “B’s Ballpark Museum” (a small baseball museum in the suburb), “Coors Field” (home field of the Rockies), as well as the upcoming baseball game “Yankees vs Rockies” to be played at Coors Field, which is fetched from Y!Sports. Example 1 represents one out of three queries on Y!Travel. However, the traditional information retrieval approach fails for it because there are often many objects that are semantically relevant to John’s query and no ranking mechanism (e.g., tf-idf measure) based on pure semantic relevance can differentiate them. It is therefore imperative for the system to incorporate social relevance, which considers John’s social profile and connections, to decide which attractions he will prefer. Essentially, information discovery on social content sites requires the integration of two major paradigms: semantic relevance with respect to a query and social relevance in the spirit of recommendations. The former scopes the discovery to information relevant to John’s current needs as expressed by him, while the latter identifies the information most appealing to John as a user. Indeed, “B’s Ballpark Museum” may not be a major attraction, yet John, being a baseball fan, is likely to enjoy a visit to it. Example 1 further illustrates another important desideratum: the need to retrieve relevant information from external social or content sites that are physically and administratively separate from Y!Travel, which is becoming possible because of various initiatives like OpenSocial Azad university of Kurdistan

Insights from the Examples Integration of three major paradigms for discovery social content sites: 1. Keyword search 2. Database-style querying 3. Recommendations Personalized search Faceted search Azad university of Kurdistan

Information organizer Information discoverer Social Scope Platform Information Presentation result selector Information organizer User Interface Information Discovery Query / Result Social Content Admin Content analyzer Information discoverer User Activity Manager Data Manager Content Management Social Content Graph Activities Content Integrator OpenSocial API OpenSocial API Facebook Y! IM Y! Sports Azad university of Kurdistan

Architectural Vision The core is the social content graph users, objects, and various connections among them Information in the graph locally owned ( destinations in Y! Travel) Externally integrated ( friendship connection obtained from Facebook ) derived ( links describing similarities between users) در هسته اصلی آن گراف محتوایی اجتماعی وجود دارد که نشان دهنده کاربران و موضوعات و ارتباطات متنوع بین آنها است اطلاعات موجود در گراف شامل : 1- محلی است ( مانند مقصد ها) 2- ارتباطات یکپارچه خارجی ( رابطه دوستی در فیس بوک) 3- اطلاعات مشتق شده ( لینک های که شباهت بین کاربران را توصیف می کند) Azad university of Kurdistan

Three layers of SocialScope system Content Management Information Discovery major goal: efficient and flexible mechanism logical algebra Each operator in the algebra takes social content graphs as input and outputs a social content graph Information Presentation هدف اصلی لایه دو (کشف اطلاعات) : ایجاد یک راهکار منعطف و کاربردی برای ساختن یک گراف محتوایی اجتماعی است Azad university of Kurdistan

Content Management Content Integrator Data Manager Activity Manager facilitate the incorporation of social info from remote sites Data Manager maintenance and retrieval of the social content graph Activity Manager when and how refresh parts of the social graph Categorizing users based on their activities دو وظیفه اصلی دارد : 1- تلفیق اطلاعات اجتماعی را با سایتهای ی از راه دور از طریق بخش اول آسان می کند 2- نگهداری و بازیابی گرافهای محتوای اجتماعی از طریق بخش دوم انجام می شود علاوه بر این نیز از طریق بخش سوم به وسیله دسته بندی کردن کاربران بر اساس فعالیتهایشان کمک می کند که تصمیم بگیرند کی و چگونه فسمتهایی از گراف را تازه و بروز کنند Azad university of Kurdistan

Content Management three major categories of data: site content users’ social profiles and connections users’ site-specific social activities -site content is the content that users are interested in when they visit the social content site -Social profiles and connections are the information regarding the users themselves (e.g., name, education, etc.) and their explicit social connections (e.g., friends, classmates, colleagues, etc.) -site-specific social activities are the activities users perform on the site content. For example, in Y! Travel, users visit and browse destinations How to effectively and efficiently manage the three categories of data is at the heart of challenges to be addressed by the Content Management layer of our SocialScope system Azad university of Kurdistan

Information Discovery Content Analyzer derives new nodes and links through various analyses of the raw social content graph automatically by the system itself Social Content Administrator Information Discoverer Meaningful Social Graph (MSG) این بخش تحلیل گر محتوا : گره های جدید و لینک ها را از طریق تحلیل های گوناگونی که بر روی گراف های محتوایی اجتماعی انجام می دهد مشتق می شود که این تحلیل یا به صورت اتوماتیک از طریق خود سیستم انجام می گیرد یا از طرف مدیر محتوای اجتماعی بخش دوم : پرس و جو های کاربران را تجزیه می کند و یک نمایش داخلی را برای آنها شکل می دهد و آنها را بر روی گراف محتوای اجتماعی ارزیابی می کند که نتیجه تمام این کارها به یک گراف پر معنی محتوای اجتماعی تبدیل می شود Azad university of Kurdistan

Information Presentation MSG as input dynamically organizes the results Information Organizer and Result Selector grouping Social Grouping ,Topical Grouping , Structural Grouping Ranking identifies appropriate mechanisms for ranking and selecting results به طور پویا نتایجی را سازماندهی می کند که کاربران بتوانند اکتشافات موثری داشته باشند موضوعات مناسبی ( ساختاری یا اجتماعی ) را برای نتا یج گروپینگ آماده می کند مکانیزمهای مناسبی برای انتخاب کردن نتایجی که از گروهای مختلف بدست می آید را شناسایی می کند زمانی هم که چندین گروههای ارائه وجود دارند بخش سازماندهی اطلاعات تصمیم می گیرد که کدام گروه بیشتر به کاربران مربوط است و به آن اطلاعات نیاز دارد Azad university of Kurdistan

Information Presentation The right presentation can help a user explore the information more effectively, especially when she is not sure about exactly what she wants Our vision is to build : dynamic result exploration framework recommender systems: presentation is an important aspect has direct implications on building users’ trust -In search, presentation is primarily in the form of a single ranked list of results, where a result’s rank reflects its degree of relevance to the input query -In recommender systems, presentation is an important aspect and has direct implications on building users’ trust and giving them incentives to participate in more activities -The rich activities and user connections provide lots of opportunities for generating recommendations Azad university of Kurdistan

Data And Query Model We model an instance of a social content site as a social content graph Consists of nodes and links Connections and activities physical and abstract entities User Topics Friendship and tagging action Azad university of Kurdistan

Data And Query Model flexible (schema-less) typing system the type attribute have multiple values n1 = {id=1; type=‘user, traveler’; name=‘John’} catalog of basic types user, item, topic, group for nodes connect (e.g., friend), act (e.g., tag, review, click,etc.), match, belong for links n2 = {id=2; type=‘item, city’; name=‘Denver’; keywords=‘skiing’} are two nodes representing our traveler John and the city Denver, respectively, in Example 1. Similarly, l12(n1, n2) = {id=12;type=‘act, tag’; date=‘2008-8-2’; tags=‘rockies baseball’} is a link recording the activity that John tagged Denver with tags ‘rockies baseball Azad university of Kurdistan

Data And Query Model Social Content Graph overlay of sub-graphs activity graph network graph topical graph Queries Users interact with SocialScope by specifying a query on content and structure the activity graph, which maintains users’ activities on items the network graph, which maintains social connection the topical graph, which maintains links from users or items to derived semantic groups or topics. the term structure refers to the attribute/value pairs associated with nodes and links. Azad university of Kurdistan

Logical Algebra Basic operators Node Selection (σN), Link Selection (σL) Composition, Semi-Join Node Aggregation, Link Aggregation Example search - Each operator in the algebra takes social content graphs as input and outputs a social content graph - Both operators Node Selection (σN), Link Selection (σL) take a condition C and an optional scoring function S as parameters, and a (social content) graph as input - The condition C consists of a list of structural conditions (e.g., {type=‘city’, rating‘0.5’}) and a set of keywords (e.g., ‘Denver attraction’) Both Composition and Semi-Join “connect” links in their input graphs. However, composition generates new links while semi-join simply filters away unwanted links. -One important feature of aggregation is the creation of new information (aggregation results) that need to be stored and maintained. -the aggregation function takes as input a collection of links and produces as output a value to be associated with the attribute a t t -a t t is the destination attribute -two classes of aggregations SAF map a set of links to a set of scalars NAF map a set of links to a numerical scalar value -The definition of the Link Aggregation operator is analogous to Node Aggregation except for two major differences: First, link aggregation changes the structure of an input graph: it replaces a set of links between a given src and tgt node by a new link. Secondly, the result of the aggregate computation is assigned as a destination attribute of the newly created link. Azad university of Kurdistan

A Simple Search Task John’s friends People visited Denver who visited Denver Their activities Azad university of Kurdistan

Model for Social Content Management -Decentralized Model: In this model, each social content site maintains their own social information, including storing the user profiles and social connections, and effectively manages the entire social content graph internally -social graph decentralization means it is necessary for users to establish their social connections multiple times on many different sites, even though most of those connections are the same. -Decentralization establishing a social graph with critical mass is incredibly difficult -Closed Cartel Model In this model, users establish and maintain their social profiles and connections at a few of the dominant social sites and let those sites or third-party applications, which are developed specifically for those sites, fulfill their content needs. Facebook is the prime example of this model. -There are two major implications for users: First, users no longer have to maintain many social profiles and establish the same social connections at many different sites, which is a significant improvement over the Decentralized Model. Second, however, they are forced to have a central online social presence, without which they won’t even have access to the contents otherwise would have been available on content sites. -Decentralized Model is being replaced by the Cartel models -which Cartel model will eventually come out on top -small niche content sites (e.g., your neighborhood reading group) will prefer the Closed Cartel model for ease of management -While larger content sites (e.g., New York Times and Y!Travel) would prefer the Open Cartel model Azad university of Kurdistan

Conclusion social content sites will increasingly become a part of the our online life we proposed SocialScope, a logical architecture three layers an algebraic framework three main categories of data ways of presenting information help user understand the large variety of content discovered from social content sites Azad university of Kurdistan

Strong point Logical architecture Information discovery over social content site Algebraic framework Azad university of Kurdistan

weakness Prototype and needs work Azad university of Kurdistan

Questions? Azad university of Kurdistan