Debranding in Fantasy Realms: Perceived Marketing Opportunities within the Virtual World

This paper discusses the application of the concept of debranding within immersive virtual environments. In particular the issue of the media richness and vividness of experience is considered in these experience realms that may not be conducive to traditional branding invasive strategies. Brand equity is generally seen to be the desired outcome of branding strategies and the authors suggest that unless the virtual domains are considered as sacred spaces then brand equity may be compromised. The application of the above concepts is applied to the differing social spaces that operate within the different experience realms. The ideas of resonance, presence and interactivity are considered here. They lead to the development of a constructed positioning by the participants. Through the process of debranding, marketers may be able to enter these sacred spaces without negative impact to the brand. Perception of these virtual spaces was found to be partially congruent with this approach to branding. It thus presents a number of challenges for the owners of such virtual spaces and also virtual worlds in increasing the commercial utilization of investment in these environments

We Could, but Should We? Ethical Considerations for Providing Access to GeoCities and Other Historical Digital Collections

We live in an era in which the ways that we can make sense of our past are evolving as more artifacts from that past become digital. At the same time, the responsibilities of traditional gatekeepers who have negotiated the ethics of historical data collection and use, such as librarians and archivists, are increasingly being sidelined by the system builders who decide whether and how to provide access to historical digital collections, often without sufficient reflection on the ethical issues at hand. It is our aim to better prepare system builders to grapple with these issues. This paper focuses discussions around one such digital collection from the dawn of the web, asking what sorts of analyses can and should be conducted on archival copies of the GeoCities web hosting platform that dates to 1994.This research was supported by the Natural Sciences and Engineering Research Council of Canada, the Social Sciences and Humanities Research Council of Canada, the US National Science Foundation (grants 1618695 and 1704369), the Andrew W. Mellon Foundation, Start Smart Labs, and Compute Canada

Video Data Visualization System: Semantic Classification And Personalization

We present in this paper an intelligent video data visualization tool, based on semantic classification, for retrieving and exploring a large scale corpus of videos. Our work is based on semantic classification resulting from semantic analysis of video. The obtained classes will be projected in the visualization space. The graph is represented by nodes and edges, the nodes are the keyframes of video documents and the edges are the relation between documents and the classes of documents. Finally, we construct the user's profile, based on the interaction with the system, to render the system more adequate to its references.Comment: graphic

Information access tasks and evaluation for personal lifelogs

Emerging personal lifelog (PL) collections contain permanent digital records of information associated with individuals’ daily lives. This can include materials such as emails received and sent, web content and other documents with which they have interacted, photographs, videos and music experienced passively or created, logs of phone calls and text messages, and also personal and contextual data such as location (e.g. via GPS sensors), persons and objects present (e.g. via Bluetooth) and physiological state (e.g. via biometric sensors). PLs can be collected by individuals over very extended periods, potentially running to many years. Such archives have many potential applications including helping individuals recover partial forgotten information, sharing experiences with friends or family, telling the story of one’s life, clinical applications for the memory impaired, and fundamental psychological investigations of memory. The Centre for Digital Video Processing (CDVP) at Dublin City University is currently engaged in the collection and exploration of applications of large PLs. We are collecting rich archives of daily life including textual and visual materials, and contextual context data. An important part of this work is to consider how the effectiveness of our ideas can be measured in terms of metrics and experimental design. While these studies have considerable similarity with traditional evaluation activities in areas such as information retrieval and summarization, the characteristics of PLs mean that new challenges and questions emerge. We are currently exploring the issues through a series of pilot studies and questionnaires. Our initial results indicate that there are many research questions to be explored and that the relationships between personal memory, context and content for these tasks is complex and fascinating

Identifying the Bounds of an Internet Resource

Systems for retrieving or archiving Internet resources often assume a URL acts as a delimiter for the resource. But there are many situations where Internet resources do not have a one-to-one mapping with URLs. For URLs that point to the first page of a document that has been broken up over multiple pages, users are likely to consider the whole article as the resource, even though it is spread across multiple URLs. Comments, tags, ratings, and advertising might or might not be perceived as part of the resource whether they are retrieved as part of the primary URL or accessed via a link. Understanding what people perceive as part of a resource is necessary prior to developing algorithms to detect and make use of resource boundaries. A pilot study examined how content similarity, URL similarity, and the combination of the two matched human expectations. This pilot study showed that more nuanced techniques were needed that took into account the particular content and context of the resource and related content. Based on the lessons from the pilot study, a study was performed focused on two research questions: (1) how particular relationships between the content of pages effect expectations and (2) how encountered implementations of saving and perceptions of content value relate to the notion of internet resource bounds. Results showed that human expectations are affected by expected relationships, such as two web pages showing parts of the same news article. They are also affected when two content elements are part of the same set of content, as is the case when two photos are presented as members of the same collection or presentation. Expectations were also affected by the role of the content – advertisements presented alongside articles or photos were less likely to be considered as part of a resource. The exploration of web resource boundaries found that people’s assessments of resource bounds rely on understanding relationships between content fragments on the same web page and between content fragments on different web pages. These results were in the context of personal archiving scenarios. Would institutional archives have different expectations? A follow-on study gathered perceptions in the context of institutional archiving questions to explore whether such perceptions change based on whether the archive is for personal use or is institutional in nature. Results show that there are similar expectations for preserving continuations of the main content in personal and institutional archiving scenarios. Institutional archives are more likely to be expected to preserve the context of the main content, such as additional linked content, advertisements, and author information. This implies alternative resource bounds based on the type of content, relationships between content elements, and the type of archive in consideration. Based on the predictive features that gathered, an automatic classification for determining if two pieces of content should be considered as part of the same resource was designed. This classifier is an example of taking into account the features identified as important in the studies of human perceptions when developing techniques that bound materials captured during the archiving of online resources

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

Wearing Many (Social) Hats: How Different are Your Different Social Network Personae?

This paper investigates when users create profiles in different social networks, whether they are redundant expressions of the same persona, or they are adapted to each platform. Using the personal webpages of 116,998 users on About.me, we identify and extract matched user profiles on several major social networks including Facebook, Twitter, LinkedIn, and Instagram. We find evidence for distinct site-specific norms, such as differences in the language used in the text of the profile self-description, and the kind of picture used as profile image. By learning a model that robustly identifies the platform given a user's profile image (0.657--0.829 AUC) or self-description (0.608--0.847 AUC), we confirm that users do adapt their behaviour to individual platforms in an identifiable and learnable manner. However, different genders and age groups adapt their behaviour differently from each other, and these differences are, in general, consistent across different platforms. We show that differences in social profile construction correspond to differences in how formal or informal the platform is.Comment: Accepted at the 11th International AAAI Conference on Web and Social Media (ICWSM17

Activity-driven content adaptation for effective video summarisation

In this paper, we present a novel method for content adaptation and video summarization fully implemented in compressed-domain. Firstly, summarization of generic videos is modeled as the process of extracted human objects under various activities/events. Accordingly, frames are classified into five categories via fuzzy decision including shot changes (cut and gradual transitions), motion activities (camera motion and object motion) and others by using two inter-frame measurements. Secondly, human objects are detected using Haar-like features. With the detected human objects and attained frame categories, activity levels for each frame are determined to adapt with video contents. Continuous frames belonging to same category are grouped to form one activity entry as content of interest (COI) which will convert the original video into a series of activities. An overall adjustable quota is used to control the size of generated summarization for efficient streaming purpose. Upon this quota, the frames selected for summarization are determined by evenly sampling the accumulated activity levels for content adaptation. Quantitative evaluations have proved the effectiveness and efficiency of our proposed approach, which provides a more flexible and general solution for this topic as domain-specific tasks such as accurate recognition of objects can be avoided