Facets of User-Assigned Tags and Their Effectiveness in Image Retrieval

This study aims to consider the value of user-assigned image tags by comparing the facets that are represented in image tags with those that are present in image queries to see if there is a similarity in the way that users describe and search for images

Pictures in words : indexing, folksonomy and representation of subject content in historic photographs

Subject access to images is a major issue for image collections. Research is needed to understand how indexing and tagging contribute to make the subjects of historic photographs accessible. This thesis firstly investigates the evidence of cognitive dissonance between indexers and users in the way they attribute subjects to historic photographs, and, secondly, how indexers and users might work together to enhance subject description. It analyses how current indexing and social tagging represent the subject content of historic photographs. It also suggests a practical way indexers can work with taggers to deal with the classic problem of resource constraints and to enhance metadata to make photo collections more accessible. In an original application of the Shatford/Panofsky classification matrix within the applications domain of historic images, patterns of subject attribution are explored between taggers and professional indexers. The study was conducted in two stages. The first stage (Studies A to D) investigated how professional indexers and taggers represent the subject content of historic photographs and revealed differences based on Shatford/Panofsky. The indexers (Study A) demonstrated a propensity for specific and generic subjects and almost complete avoidance of abstracts. In contrast, a pilot study with users (Study B) and with baseline taggers (Studies C and D) showed their propensity for generics and equal inclination to specifics and abstracts. The evidence supports the conclusion that indexers and users approach the subject content of historic photographs differently, demonstrating cognitive dissonance, a conflict between how they appear to think about and interpret images. The second stage (Study E) demonstrated that an online training intervention affected tagging behaviour. The intervention resulted in increased tagging and fuller representation of all subject facets according to the Shatford/Panofsky classification matrix. The evidence showed that trained taggers tagged more generic and abstract facets than untrained taggers. Importantly, this suggests that training supports the annotation of the higher levels of subject content and so potentially provides enhanced intellectual access. The research demonstrated a practical way institutions can work with taggers to extend the representation of subject content in historic photographs. Improved subject description is critical for intellectual access and retrieval in the cultural heritage space. Through systematic application of the training method a richer corpus of descriptors might be created that enhances machine based information retrieval via automatic extraction

VideoTag: Encouraging the Effective Tagging of Internet Videos Through Tagging Games

A thesis submitted in partial fulfillment of the requirements of the University of Wolverhampton for the degree of Doctor of PhilosophyAbstract The tags and descriptions entered by video owners in video sharing sites are typically inadequate for retrieval purposes, yet the majority of video search still uses this text. This problem is escalating due to the ease with which users can self-publish videos, generating masses that are poorly labelled and poorly described. This thesis investigates how users tag videos and whether video tagging games can solve this problem by generating useful sets of tags. A preliminary study investigated tags in two social video sharing sites, YouTube and Viddler. YouTube contained many irrelevant tags because the system does not encourage users to tag their videos and does not promote tags as useful. In contrast, using tags as the sole means of categorisation in Viddler motivated users to enter a higher proportion of relevant tags. Poor tags were found in both systems, however, highlighting the need to improve video tagging. In order to give users incentives to tag videos, the VideoTag project in this thesis developed two tagging games, Golden Tag and Top Tag, and one non-game tagging system, Simply Tag, and conducted two experiments with them. In the first experiment VideoTag was a portal to play video tagging games whereas in the second experiment it was a portal to curate collections of special interest videos. Users preferred to tag videos using games, generating tags that were relevant to the videos and that covered a range of tag types that were descriptive of the video content at a predominately specific, objective level. Users were motivated by interest in the content rather than by game elements, and content had an effect on the tag types used. In each experiment, users predominately tagged videos using objective language, with a tendency to use specific rather than basic tags. There was a significant difference between the types of tags entered in the games and in Simply Tag, with more basic, objective vocabulary entered into the games and more specific, objective language entered into the non-game system. Subjective tags were rare but were more frequent in Simply Tag. Gameplay also had an influence on the types of tags entered; Top Tag generated more basic tags and Golden Tag generated more specific and subjective tags. Users were not attracted to use VideoTag by the games alone. Game mechanics had little impact on motivations to use the system. VideoTag used YouTube videos, but could not upload the tags to YouTube and so users could see no benefit for the tags they entered, reducing participation. Specific interest content was more of a motivator for use than games or tagging and that this warrants further research. In the current game-saturated climate, gamification of a video tagging system may therefore be most successful for collections of videos that already have a committed user base.University of Wolverhampto