Semantic Stability in Social Tagging Streams

One potential disadvantage of social tagging systems is that due to the lack of a centralized vocabulary, a crowd of users may never manage to reach a consensus on the description of resources (e.g., books, users or songs) on the Web. Yet, previous research has provided interesting evidence that the tag distributions of resources may become semantically stable over time as more and more users tag them. At the same time, previous work has raised an array of new questions such as: (i) How can we assess the semantic stability of social tagging systems in a robust and methodical way? (ii) Does semantic stabilization of tags vary across different social tagging systems and ultimately, (iii) what are the factors that can explain semantic stabilization in such systems? In this work we tackle these questions by (i) presenting a novel and robust method which overcomes a number of limitations in existing methods, (ii) empirically investigating semantic stabilization processes in a wide range of social tagging systems with distinct domains and properties and (iii) detecting potential causes for semantic stabilization, specifically imitation behavior, shared background knowledge and intrinsic properties of natural language. Our results show that tagging streams which are generated by a combination of imitation dynamics and shared background knowledge exhibit faster and higher semantic stability than tagging streams which are generated via imitation dynamics or natural language streams alone

The impact of image descriptions on user tagging behavior: A study of the nature and functionality of crowdsourced tags

Crowdsourcing has emerged as a way to harvest social wisdom from thousands of volunteers to perform a series of tasks online. However, little research has been devoted to exploring the impact of various factors such as the content of a resource or crowdsourcing interface design on user tagging behavior. Although images' titles and descriptions are frequently available in image digital libraries, it is not clear whether they should be displayed to crowdworkers engaged in tagging. This paper focuses on offering insight to the curators of digital image libraries who face this dilemma by examining (i) how descriptions influence the user in his/her tagging behavior and (ii) how this relates to the (a) nature of the tags, (b) the emergent folksonomy, and (c) the findability of the images in the tagging system. We compared two different methods for collecting image tags from Amazon's Mechanical Turk's crowdworkers - with and without image descriptions. Several properties of generated tags were examined from different perspectives: diversity, specificity, reusability, quality, similarity, descriptiveness, and so on. In addition, the study was carried out to examine the impact of image description on supporting users' information seeking with a tag cloud interface. The results showed that the properties of tags are affected by the crowdsourcing approach. Tags from the "with description" condition are more diverse and more specific than tags from the "without description" condition, while the latter has a higher tag reuse rate. A user study also revealed that different tag sets provided different support for search. Tags produced "with description" shortened the path to the target results, whereas tags produced without description increased user success in the search task

Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis

Collaborative tagging is a simple and effective method for organizing and sharing web resources using human created metadata. It has arisen out of the need for an efficient method of personal organization, as the number of digital resources in everyday lives increases. While tagging has become a proven organization scheme through its popularity and widespread use on the Web, little is known about its implications and how it may effectively be applied in different situations. This is due to the fact that tagging has evolved through several iterations of use on social software websites, rather than through a scientific or an engineering design process. The research presented in this thesis, through investigations in the domain of e-learning, seeks to understand more about the scientific nature of collaborative tagging through a number of human subject studies. While broad in scope, touching on issues in human computer interaction, knowledge representation, Web system architecture, e-learning, metadata, and information visualization, this thesis focuses on how collaborative tagging can supplement the growing metadata requirements of e-learning. I conclude by looking at how the findings may be used in future research, through using information based in the emergent social networks of social software, to automatically adapt to the needs of individual users

Wayang Authoring: A Web-based Authoring Tool for Visual Storytelling for Children

This research focuses on the development of the Wayang Authoring tool as it aims to assist children in creating and performing stories, developing an appreciation for cultural artifacts, and enhancing intercultural empathy while building a young storyteller community in a virtual world. This study seeks a framework of interaction design of an authoring media which is appropriate to support children s narrative development. The concept of the tool is based on the narrative element of the ancient Indonesian art form wayang, a traditional two dimensional shadow puppet theater. To understand the user s requirements and the cultural dimension, children and professional story performers who use wayang have been involved in the design process. In order to evaluate the tool, several workshops have been conducted with children from different cultural backgrounds as well as with their teachers. Wayang Authoring is composed of three elements: the imagination-building element, the creative acting element and the social interaction element. Children take existing materials as an inspiration tool, imagine what they themselves want to tell, create a story based on their own ideas, play with their creations, share their stories and creations with others, and reflect on their experiences at the end. This virtual creative production tool is expected to provide a space for young people to change their role from a simple user to a (co-)creator in the virtual and narrative worlds. The core contributions are in the field of web technology for storytelling. The uses of web-based authoring media enable children to put themselves into the process of developing stories. When they are connecting stories, they are connected and immersed with other children as well. They have to act and play by themselves or with others within the stories in order to experience the narratives. They train to have the skills to interact, to share their ideas and to collaborate constructively. This makes it possible for them to participate in today s media-driven culture. This research found that a better understanding of how stories are crafted and brought to life in a performance tradition offers a better design of interaction of an authoring media. The handling of cultural artifacts supports the ability to understand different cultural codes and to pursue the learning process surrounding the original culture behind these artifacts

Making digital history: The impact of digitality on public participation and scholarly practices in historical research

This thesis investigates tow key questions: firstly, how do two broad groups - academic, family and local historians, and the public - evaluate, use, and contribute to digital history resources? And consequently, what impact have digital technologies had on public participation and scholarly practices in historical research? Analysing the impact of design on participant experiences and the reception of digital historiography by demonstrating the value of methods drawn from human-computer interaction, including heuristic evaluation, trace ethnography and semi-structured interviews. This thesis also investigates the relationship between heritage crowdsourcing projects (which ask the public to help with meaningful, inherently rewarding tasks that contribute to a shared, significant goal or research interest related to cultural heritage collections or knowledge) and the development of historical skills and interests. It situates crowdsourcing and citizen history within the broader field of participatory digital history and then focuses on the impact of digitality on the research practices of faculty and community historians. Chapter 1 provides an overview of over 400 digital history projects aimed at engaging the public or collecting, creating or enhancing records about historical materials for scholarly and general audiences. Chapter 2 discusses design factors that may influence the success of crowdsourcing projects. Following this, Chapter 3 explores the ways in which some crowdsourcing projects encourage deeper engagement with history or science, and the role of communities of practice in citizen history. Chapter 4 shifts our focus from public participation to scholarly practices in historical research, presenting the results of interviews conducted with 29 faculty and community historians. Finally, the Conclusion draws together the threads that link public participation and scholarly practices, teasing out the ways in which the practices of discovering, gathering, creating and sharing historical materials and knowledge have been affected by digital methods, tools and resources

Personalized Recommendations Based On Users’ Information-Centered Social Networks

The overwhelming amount of information available today makes it difficult for users to find useful information and as the solution to this information glut problem, recommendation technologies emerged. Among the several streams of related research, one important evolution in technology is to generate recommendations based on users’ own social networks. The idea to take advantage of users’ social networks as a foundation for their personalized recommendations evolved from an Internet trend that is too important to neglect – the explosive growth of online social networks. In spite of the widely available and diversified assortment of online social networks, most recent social network-based recommendations have concentrated on limited kinds of online sociality (i.e., trust-based networks and online friendships). Thus, this study tried to prove the expandability of social network-based recommendations to more diverse and less focused social networks. The online social networks considered in this dissertation include: 1) a watching network, 2) a group membership, and 3) an academic collaboration network. Specifically, this dissertation aims to check the value of users’ various online social connections as information sources and to explore how to include them as a foundation for personalized recommendations. In our results, users in online social networks shared similar interests with their social partners. An in-depth analysis about the shared interests indicated that online social networks have significant value as a useful information source. Through the recommendations generated by the preferences of social connection, the feasibility of users’ social connections as a useful information source was also investigated comprehensively. The social network-based recommendations produced as good as, or sometimes better, suggestions than traditional collaborative filtering recommendations. Social network-based recommendations were also a good solution for the cold-start user problem. Therefore, in order for cold-start users to receive reasonably good recommendations, it is more effective to be socially associated with other users, rather than collecting a few more items. To conclude, this study demonstrates the viability of multiple social networks as a means for gathering useful information and addresses how different social networks of a novelty value can improve upon conventional personalization technology