Searching for salvation: An analysis of US religious searching on the World Wide Web

The goals of this research were to answer three questions. How predominant is religious searching online? How do people interact with Web search engines when searching for religious information? How effective are these interactions in locating relevant information? Specifically, referring to a US demographic, we analyzed five data sets from Web search engine, collected between 1997 and 2005, of over a million queries each in order to investigate religious searching on the Web. Results point to four key findings. First, there is no evidence of a decrease in religious Web-searching behaviors. Religious interest is a persistent topic of Web searching. Second, those seeking religious information on the Web are becoming slightly more interactive in their searching. Third, there is no evidence for a move away from mainstream religions toward non-mainstream religions since the majority of the search terms are associated with established religions. Fourth, our work does not support the hypothesis that traditional religious affiliation is associated with lower adoption of or sophistication with technology. These factors point to the Web as a potentially usefully communication medium for a variety of religious organizations. © 2009 Elsevier Ltd. All rights reserved.

Effect of topic domain and task type on Web image searching

Many user studies in Web information searching have found the significant effect of task types on search strategies. However, little attention was given to Web image searching strategies, especially the query reformulation activity despite that this is a crucial part in Web image searching. In this study, we investigated the effects of topic domains and task types on user’s image searching behavior and query reformulation strategies. Some significant differences in user’s tasks specificity and initial concepts were identified among the task domains. Task types are also found to influence participant’s result reviewing behavior and query reformulation strategies.

Modelling users' contextual querying behaviour for web image searching

The rapid growth of visual information on Web has led to immense interest in multimedia information retrieval (MIR). While advancement in MIR systems has achieved some success in specific domains, particularly the content-based approaches, general Web users still struggle to find the images they want. Despite the success in content-based object recognition or concept extraction, the major problem in current Web image searching remains in the querying process. Since most online users only express their needs in semantic terms or objects, systems that utilize visual features (e.g., color or texture) to search images create a semantic gap which hinders general users from fully expressing their needs. In addition, query-by-example (QBE) retrieval imposes extra obstacles for exploratory search because users may not always have the representative image at hand or in mind when starting a search (i.e. the page zero problem). As a result, the majority of current online image search engines (e.g., Google, Yahoo, and Flickr) still primarily use textual queries to search. The problem with query-based retrieval systems is that they only capture users’ information need in terms of formal queries;; the implicit and abstract parts of users’ information needs are inevitably overlooked. Hence, users often struggle to formulate queries that best represent their needs, and some compromises have to be made. Studies of Web search logs suggest that multimedia searches are more difficult than textual Web searches, and Web image searching is the most difficult compared to video or audio searches. Hence, online users need to put in more effort when searching multimedia contents, especially for image searches. Most interactions in Web image searching occur during query reformulation. While log analysis provides intriguing views on how the majority of users search, their search needs or motivations are ultimately neglected. User studies on image searching have attempted to understand users’ search contexts in terms of users’ background (e.g., knowledge, profession, motivation for search and task types) and the search outcomes (e.g., use of retrieved images, search performance). However, these studies typically focused on particular domains with a selective group of professional users. General users’ Web image searching contexts and behaviors are little understood although they represent the majority of online image searching activities nowadays. We argue that only by understanding Web image users’ contexts can the current Web search engines further improve their usefulness and provide more efficient searches. In order to understand users’ search contexts, a user study was conducted based on university students’ Web image searching in News, Travel, and commercial Product domains. The three search domains were deliberately chosen to reflect image users’ interests in people, time, event, location, and objects. We investigated participants’ Web image searching behavior, with the focus on query reformulation and search strategies. Participants’ search contexts such as their search background, motivation for search, and search outcomes were gathered by questionnaires. The searching activity was recorded with participants’ think aloud data for analyzing significant search patterns. The relationships between participants’ search contexts and corresponding search strategies were discovered by Grounded Theory approach. Our key findings include the following aspects: - Effects of users' interactive intents on query reformulation patterns and search strategies - Effects of task domain on task specificity and task difficulty, as well as on some specific searching behaviors - Effects of searching experience on result expansion strategies A contextual image searching model was constructed based on these findings. The model helped us understand Web image searching from user perspective, and introduced a context-aware searching paradigm for current retrieval systems. A query recommendation tool was also developed to demonstrate how users’ query reformulation contexts can potentially contribute to more efficient searching.

Multitasking, cognitive coordination and cognitive shifts during web searching

As Web searching becomes more prolific for information access worldwide, we need to better understand users’ Web searching behaviour and develop better models of their interaction with Web search systems. Web search modelling is a significant and important area of Web research. Searching on the Web is an integral element of information behaviour and human–computer interaction. Web searching includes multitasking processes, the allocation of cognitive resources among several tasks, and shifts in cognitive, problem and knowledge states. In addition to multitasking, cognitive coordination and cognitive shifts are also important, but are under-explored aspects of Web searching. During the Web searching process, beyond physical actions, users experience various cognitive activities. Interactive Web searching involves many users’ cognitive shifts at different information behaviour levels. Cognitive coordination allows users to trade off the dependences among multiple information tasks and the resources available. Much research has been conducted into Web searching. However, few studies have modelled the nature of and relationship between multitasking, cognitive coordination and cognitive shifts in the Web search context. Modelling how Web users interact with Web search systems is vital for the development of more effective Web IR systems. This study aims to model the relationship between multitasking, cognitive coordination and cognitive shifts during Web searching. A preliminary theoretical model is presented based on previous studies. The research is designed to validate the preliminary model. Forty-two study participants were involved in the empirical study. A combination of data collection instruments, including pre- and post-questionnaires, think-aloud protocols, search logs, observations and interviews were employed to obtain users’ comprehensive data during Web search interactions. Based on the grounded theory approach, qualitative analysis methods including content analysis and verbal protocol analysis were used to analyse the data. The findings were inferred through an analysis of questionnaires, a transcription of think-aloud protocols, the Web search logs, and notes on observations and interviews. Five key findings emerged. (1) Multitasking during Web searching was demonstrated as a two-dimensional behaviour. The first dimension was represented as multiple information problems searching by task switching. Users’ Web searching behaviour was a process of multiple tasks switching, that is, from searching on one information problem to searching another. The second dimension of multitasking behaviour was represented as an information problem searching within multiple Web search sessions. Users usually conducted Web searching on a complex information problem by submitting multiple queries, using several Web search systems and opening multiple windows/tabs. (2) Cognitive shifts were the brain’s internal response to external stimuli. Cognitive shifts were found as an essential element of searching interactions and users’ Web searching behaviour. The study revealed two kinds of cognitive shifts. The first kind, the holistic shift, included users’ perception on the information problem and overall information evaluation before and after Web searching. The second kind, the state shift, reflected users’ changes in focus between the different cognitive states during the course of Web searching. Cognitive states included users’ focus on the states of topic, strategy, evaluation, view and overview. (3) Three levels of cognitive coordination behaviour were identified: the information task coordination level, the coordination mechanism level, and the strategy coordination level. The three levels of cognitive coordination behaviour interplayed to support multiple information tasks switching. (4) An important relationship existed between multitasking, cognitive coordination and cognitive shifts during Web searching. Cognitive coordination as a management mechanism bound together other cognitive processes, including multitasking and cognitive shifts, in order to move through users’ Web searching process. (5) Web search interaction was shown to be a multitasking process which included information problems ordering, task switching and task and mental coordinating; also, at a deeper level, cognitive shifts took place. Cognitive coordination was the hinge behaviour linking multitasking and cognitive shifts. Without cognitive coordination, neither multitasking Web searching behaviour nor the complicated mental process of cognitive shifting could occur. The preliminary model was revisited with these empirical findings. A revised theoretical model (MCC Model) was built to illustrate the relationship between multitasking, cognitive coordination and cognitive shifts during Web searching. Implications and limitations of the study are also discussed, along with future research work.

Web searching interaction model based on user cognitive styles

As more and more information is available on the Web finding quality and reliable information is becoming harder. To help solve this problem, Web search models need to incorporate users’ cognitive styles. This paper reports the preliminary results from a user study exploring the relationships between Web users’ searching behavior and their cognitive style. The data was collected using a questionnaire, Web search logs and think-aloud strategy. The preliminary findings reveal a number of cognitive factors, such as information searching processes, results evaluations and cognitive style, having an influence on users’ Web searching behavior. Among these factors, the cognitive style of the user was observed to have a greater impact. Based on the key findings, a conceptual model of Web searching and cognitive styles is presented.

Patterns of query reformulation during web searching

Query reformulation is a key user behavior during Web search. Our research goal is to develop predictive models of query reformulation during Web searching. This article reports results from a study in which we automatically classified the query-reformulation patterns for 964,780 Web searching sessions, composed of 1,523,072 queries, to predict the next query reformulation. We employed an n-gram modeling approach to describe the probability of users transitioning from one query-reformulation state to another to predict their next state. We developed first-, second-, third-, and fourth-order models and evaluated each model for accuracy of prediction, coverage of the dataset, and complexity of the possible pattern set. The results show that Reformulation and Assistance account for approximately 45% of all query reformulations; furthermore, the results demonstrate that the first- and second-order models provide the best predictability, between 28 and 40% overall and higher than 70% for some patterns. Implications are that the n-gram approach can be used for improving searching systems and searching assistance.

Predicting query reformulation during web searching

This paper reports results from a study in which we automatically classified the query reformulation patterns for 964,780 Web searching sessions (composed of 1,523,072 queries) in order to predict what the next query reformulation would be. We employed an n-gram modeling approach to describe the probability of searchers transitioning from one query reformulation state to another and predict their next state. We developed first, second, third, and fourth order models and evaluated each model for accuracy of prediction. Findings show that Reformulation and Assistance account for approximately 45 percent of all query reformulations. Searchers seem to seek system searching assistant early in the session or after a content change. The results of our evaluations show that the first and second order models provided the best predictability, between 28 and 40 percent overall, and higher than 70 percent for some patterns. Implications are that the n-gram approach can be used for improving searching systems and searching assistance in real time.

A study and comparison of multimedia Web searching : 1997-2006

Searching for multimedia is an important activity for users of Web search engines. Studying user's interactions with Web search engine multimedia buttons, including image, audio, and video, is important for the development of multimedia Web search systems. This article provides results from a Weblog analysis study of multimedia Web searching by Dogpile users in 2006. The study analyzes the (a) duration, size, and structure of Web search queries and sessions; (b) user demographics; (c) most popular multimedia Web searching terms; and (d) use of advanced Web search techniques including Boolean and natural language. The current study findings are compared with results from previous multimedia Web searching studies. The key findings are: (a) Since 1997, image search consistently is the dominant media type searched followed by audio and video; (b) multimedia search duration is still short (>50% of searching episodes are <1 min), using few search terms; (c) many multimedia searches are for information about people, especially in audio search; and (d) multimedia search has begun to shift from entertainment to other categories such as medical, sports, and technology (based on the most repeated terms). Implications for design of Web multimedia search engines are discussed.

Identification of factors predicting clickthrough in Web searching using neural network analysis

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing