Chapter 4 The Future of Social Web Sites

Abstract

In recent years, there has been an explosion in the number of Social Web sites which allow the creation of knowledge through simplified user contributions via blogs, wikis, and the deployment of online social networks. As more Social Web sites form around the connections between people and their objects of interest, and as these “object‐centered networks” grow bigger and more diverse, more intuitive methods are needed for representing and navigating the objects in these sites: both within and across Social Web sites. Also, to better enable user access to multiple sites, interoperability among Social Web sites is required in terms of both the expressed data (content objects, person‐to‐person networks, etc.) and the social applications in use (e.g., widgets) on each site. This requires representation mechanisms for data and applications on the Social Web in an interoperable and extensible way. The Semantic Web provides such representation mechanisms: it can be used to link people and objects by representing the heterogeneous ties that bind us all to each other (either directly or indirectly). In this chapter, we will describe methods that build on agreed‐upon Semantic Web formats to describe people, content objects, the connections that bind them together explicitly or implicitly, and embeddable application widgets on Social Web sites, thereby enabling these sites to interoperate by appealing to some common semantics. We will also focus on how a social aspect can be added to data such as software project and widgets descriptions, so that one can combine social networking, trust, and relationship aspects with those representation models. We will also look at how developers can use the Semantic Web to augment the ways in which they create, reuse, and link content on social networking sites and Social Web sites. In particular, we will see how both data and applications can be shared on the Web, thanks to these semantics.

Introduction

Since it was founded, the Web has been used to facilitate communication not only between computers but also between people. Usenet mailing lists and Web forums allowed people to connect with each other and enabled communities to form, often around topics of interest. The social networks formed via these technologies were not explicitly stated, but were implicitly defined by the interactions of the people involved. Later, technologies such as IRC (Internet Relay Chat), instant messaging and blogging continued the trend of using the Internet to build communities.

Social networking sites (SNSs) such as Friendster (an early SNS previously popular in the US, now widely used in Asia), Orkut (Google's SNS), LinkedIn (an SNS for professional relationships), and MySpace (a music‐ and youth‐oriented service)—where explicitly stated networks of friendship form a core part of the Web site—have become part of the daily lives of millions of users, and generated huge amounts of investment since they began to appear around 2002. Since then, the popularity of these sites has grown hugely and continues to do so. Boyd and Ellison [10] recently described the history of SNSs, and suggested that in the early days of SNSs, when only the SixDegrees service existed, there simply were not enough users: “While people were already flocking to the Internet, most did not have extended networks of friends who were online.” A graph from Internet World Stats¹ shows the growth in the number of Internet users over time. Between 2000 (when SixDegrees shut down) and 2003 (when Friendster became the first successful SNS), the number of Internet users had doubled.

Content‐sharing sites with social networking functionality such as YouTube (a video‐sharing site), Flickr (for sharing images), and last.fm (a radio and music community site) have enjoyed similar popularity. The basic features of an SNS are profiles, friend's listings and commenting, often along with other features such as private messaging, discussion forums, blogging, and media uploading and sharing. Many content‐sharing sites such as Flickr and YouTube also include some social networking functionality. In addition to SNSs, other forms of Social Web sites include wikis, forums, and blogs. Some of these publish content in structured formats enabling them to be aggregated together. The Social Web or “Web 2.0” has enabled community‐based knowledge acquisition with efforts like the Wikipedia demonstrating the “wisdom of the crowds” in creating the world's largest online encyclopedia. Although it is difficult to define the exact boundaries of what structures or abstractions belong to the Social Web, a common property of such sites is that they facilitate collaboration and sharing between users with low technical barriers, although usually on single sites.

A limitation of current Social Web sites is that they are isolated from one another like islands in a sea. For example, different online discussions may contain complementary knowledge and topics, segmented parts of an answer that a person may be looking for, but people participating in one discussion do not have ready access to information about related discussions elsewhere. As more and more Social Web sites, communities, and services come online, the lack of interoperation among them becomes obvious: a set of single data silos or “stovepipes” has been created, that is, there are many sites, communities, and services that cannot interoperate with each other, where synergies are expensive to exploit, and where reuse and interlinking of data is difficult and cumbersome. The main reason for this lack of interoperation is that for the most part in the Social Web, there are still no common standards for knowledge and information exchange and interoperation available. RSS (Really Simple Syndication), a format for publishing recently updated Web content such as blog entries, could be a first solution for interoperability among Social Web sites, but it has various limitations that make it difficult to be used efficiently in such a context, as we will see later.

However, the Semantic Web effort aims to provide the tools that are necessary to define extensible and flexible standards for information exchange and interoperability. The Scientific American article from Berners‐Lee et al. [4] defined the Semantic Web as “an extension of the current Web in which information is given well‐defined meaning, better enabling computers and people to work in cooperation.” The last couple of years have seen large efforts going into the definition of the foundational standards supporting data interchange and interoperation, and currently a well‐defined Semantic Web technology stack exists, enabling the creation of defining metadata and associated vocabularies. The Semantic Web effort is in an ideal position to make Social Web sites interoperable. The application of the Semantic Web to the Social Web can lead to a “Social Semantic Web” (Fig. 1), creating a network of interlinked and semantically rich knowledge. This vision of the Web will consist of interlinked documents, data, and even applications created by the end users themselves as the result of various social interactions, and it is modeled using machine‐readable formats, so that it can be used for purposes that the current state of the Social Web cannot achieve without difficulty.

A semantic data “food chain” (see Fig. 2), that is, producers, collectors, and consumers of semantic data from social networks and Social Web sites, can lead to something greater than the sum of its parts: a social Semantic Web where the islands of the Social Web can be interconnected with semantic technologies, and Semantic Web applications are enhanced with the wealth of knowledge inherent in user‐generated content.

Applying semantic technologies to Social Web sites can greatly enhance the value and functionality of these sites. The information within these sites is forming vast and diverse networks which can benefit from Semantic Web technologies for representation and navigation. Additionally, to easily enable navigation and data portability across sites, mechanisms are required to represent data in an interoperable and extensible way. These are termed semantic data producers.

An intermediary step which may or may not be required is for the collection of semantic data. In very large sites, this may not be an issue as the information in the site may be sufficiently linked internally to warrant direct consumption after production, but in general, may users make small contributions across a range of services which can benefit from an aggregate view through some collection service. Collection services can include aggregation and consolidation systems, semantic search engines, or data lookup indexes.

The final step involves consumers of semantic data. Social networking technologies enable people to articulate their social network via friend connections. A social network can be viewed as a graph where the nodes represent individuals and the edges represent relations. Methods from graph theory can be used to study these networks, and we will describe how social network analysis (SNA) can consume semantic data from the food chain.

Also, representing social data in RDF (Resource Description Framework), a language for describing Web resources in a structured way, enables us to perform queries on a network to locate information relating to a person or people. Interlinking social data from multiple sources may give an enhanced view of information in distributed communities, and we will describe applications to consume this interlinked data.

In this chapter, we will begin by describing various social networking sites and Social Web sites, along with some of their limitations and initial approaches to leverage semantics in social networks, blogs, wikis, tagging, and software descriptions. We will discuss the representation methods that can be used by semantic producers to represent data (user profiles, feeds, content) and applications (widgets) for porting and sharing amongst users and sites. We will then describe the collection stage in a “semantic data food chain,” giving examples of queries that can be used to consolidate aggregates of data from Social Web sites. We will also discuss how trust mechanisms in consuming applications can be leveraged via the distributed social graph, so that users can decide who to accept any new data or applications from. Finally, we will give our conclusions and ideas for future work.