Richard Glassey

When complexity becomes interesting

How to provide users a positive experience during interaction with information (i.e., the “Information eXperience” (IX)) is still an open question. As a starting point, this work investigates how the emotion of interest can be influenced by modifying the complexity of the information presented to users. The appraisal theory of interest suggests a “sweet spot” where interest will be at its peak: information that is novel and complex yet still comprehensible. This “sweet spot” is approximated using two studies. Study One develops a computational model of textual complexity founded on psycholinguistic theory on processing difficulty. The model was trained and tested on 12,420 articles, achieving a classification performance of 90.87% on two classes of complexity. Study Two puts the model to its ultimate test: Its application to change the users IX. Using 18 news articles the influence of complexity on interest and its appraisals is unveiled. A structural equation model shows a positive influence of complexity on interest, yet a negative influence of comprehensibility, confirming a seemingly paradoxical relationship between complexity and interest. By showing when complexity becomes interesting, this paper shows how information systems can use the model of textual complexity to construct an interesting IX.

Interaction-based information filtering for children

This paper presents an interaction-based information filtering system designed for the needs of children accessing multiple streams of information. This is an emerging problem due to the increased information access and engagement by children for their education and entertainment, and the explosion of stream-based information sources on most topics.n It has been shown that children have difficulties formulating text-based queries and using interfaces primarily designed for adults. The in-progress system presented in this paper attempts to address these difficulties by employing an interaction-based interface that simplifies the expression of information needs and adapts itself to user interests over time. To overcome issues of content moderation, the system aggregates multiple child-friendly information feeds and performs offline processing to facilitate topic filtering. A set of standing topics are created for initial interaction and subsequent interactions are used to infer and refine which topics the child would most likely want to have presented. A simple and easy-to-use interface is presented which uses relevance information to determine the appropriate size of the document title to display to act as a relevance-cue to the user.n The planned research focuses on validating the interaction-based approach with both child and adult populations to discover the differences and similarities that may exist.

EmSe: initial evaluation of a child-friendly medical search system

When undergoing medical treatment in combination with extended stays in hospitals, children have been frequently found to develop an interest in their condition and the course of treatment. A natural means of searching for related information would be to use a web search engine. The medical domain, however, imposes several key challenges on young and inexperienced searchers, such as difficult terminology, potentially frightening topics or non-objective information offered by lobbyists or pharmaceutical companies. To address these problems, we present the design and usability study of EmSe, a search service for children in a hospital environment.

Web Search Query Assistance Functionality for Young Audiences

The Internet plays an important role in peoples daily lives. This is not only true for adults, but also holds for children; however, current web search engines are designed with adult users and their cognitive abilities in mind. Consequently, children face considerable barriers when using these information systems. In this work, we demonstrate the use of query assistance and search moderation techniques as well as appropriate interface design to overcome or mitigate these challenges.

MaSe: create your own mash-up search interface

MaSe provides a sandbox environment for high school students to create their own personalised search interface. It has been designed with two major goals in mind: (1) as a hands-on tutorial for school children, to excite them about programming and computing science through the development of a practical application, and (2) to enable children to design and create their own search interface without extensive programming knowledge or prior experience. Consequently, MaSe provides a way to ascertain what children would like from a search engine interface in an exploratory and creative way as they can create a working prototype. This approach contrasts with previous work on exploring childrens requirements of IR systems which attempts to directly elicit user needs through more traditional methods (i.e. surveys, interviews, focus groups, etc). However, we have attempted to incorporate the design guidelines for children as identified by Large (2006) into MaSe, where: we make use of bright colours, large text fonts, spell checking and the use of icons to represent search services, as well as including a thematic experience as suggested by Large (2006), with the use of a puppy avatar and puppy dog footprints.

Contextual Sentiment Analysis in Social Media Using High-Coverage Lexicon

Automatically generated sentiment lexicons offer sentiment information for a large number of terms and often at a more granular level than manually generated ones. While such rich information has the potential of enhancing sentiment analysis, it also presents the challenge of finding the best possible strategy to utilising the information. In SentiWordNet, negation terms and lexical valence shifters (i.e. intensifier and diminisher terms) are associated with sentiment scores. Therefore, such terms could either be treated as sentiment-bearing using the scores offered by the lexicon, or as sentiment modifiers that influence the scores assigned to adjacent terms. In this paper, we investigate the suitability of both these approaches applied to sentiment classification. Further, we explore the role of non-lexical modifiers common to social media and introduce a sentiment score aggregation strategy named SmartSA. Evaluation on three social media datasets show that the strategy is effective and outperform the baseline of using aggregate-and-average approach.

Finding and filtering information for children

Children face several challenges when using information access systems. These include formulating queries, judging the relevance of documents, and focusing attention on interface cues, such as query suggestions, while typing queries. It has also been shown that children want a personalised Web experience and prefer content presented to them that matches their long-term entertainment and education needs. To this end, we have developed an interaction-based information filtering system to address these challenges.

PageFetch: a retrieval game for children (and adults)

Children often struggle with information retrieval tasks as searching for information often requires a developed vocabulary and strong categorisation skills; neither of which are particularly developed in children under the age of 12. In a study conducted by Druin et al, it was found that in an experimental setting many children are often uninterested in searching for information online or are only interested in searching for information that is relevant to their personal interests. Consequently, children who were unmotivated were the least successful in completing information retrieval tasks in their study. It was suggested that a more effective means of engaging child participants in search studies must be developed in order to gain further insights into the searching behaviours of children. To this end we have developed a game called PageFetch which aims to engage children (aged 8 to 80) in completing search tasks through a fun and interactive search-like interface.

Finding interest in the stream

Interest, the curious emotion, plays a crucial role as an intrinsic motivator to encounter new things. It also plays a role in the establishment of longer term interests that people develop. Providing support for the experience of interest, and managing the development of enduring interests has potential to augment the effectiveness of information streaming applications. This poster briefly surveys ‘interest’ and considers the implications of a hypothetical Interest Machine that is able to measure interest and model interests.

Detection of news feeds items appropriate for children

Identifying child-appropriate web content is an important yet difficult classification task. This novel task is characterised by attempting to determine age/child appropriateness (which is not necessarily topic-based), despite the presence of unbalanced class sizes and the lack of quality training data with human judgements of appropriateness. Classification of feeds, a subset of web content, presents further challenges due to their temporal nature and short document format. In this paper, we discuss these challenges and present baseline results for this task through an empirical study that classifies incoming news stories as appropriate (or not) for children. We show that while the naive Bayes approach produces a higher AUC it is vulnerable to the imbalanced data problem, and that support vector machine provides a more robust overall solution. Our research shows that classifying childrens content is a non-trivial task that has greater complexities than standard text based classification. While the F-score values are consistent with other research examining age-appropriate text classification, we introduce a new problem with a new dataset.