Researchers in Human-Computer Interaction typically rely on experiments to assess the causal effects of experimental conditions on variables of interest. Although this classic approach can be very useful, it offers little help in tackling questions of causality in the kind of data that are increasingly common in HCI – capturing user behavior ‘in the wild.’ To analyze such data, model-based regressions such as cross-lagged panel models or vector autoregressions can be used, but these require parametric assumptions about the structural form of effects among the variables. To overcome some of the limitations associated with experiments and model-based regressions, we adopt and extend ‘empirical dynamic modelling’ methods from ecology that lend themselves to conceptualizing multiple users’ behavior as complex nonlinear dynamical systems. Extending a method known as ‘convergent cross mapping’ or CCM, we show how to make causal inferences that do not rely on experimental manipulations or model-based regressions and, by virtue of being non-parametric, can accommodate data emanating from complex nonlinear dynamical systems. By using this approach for multiple users, which we call ‘multiple convergent cross mapping’ or MCCM, researchers can achieve a better understanding of the interactions between users and technology – by distinguishing causality from correlation – in real-world settings.

In an empirical user study, we assessed two approaches to ranking the results from a keyword search using semantic contextual match based on Latent Semantic Analysis. These techniques involved searches initiated from words found in a seed document within a corpus. The first approach used the sentence around the search query in the document as context while the second used the entire document. With a corpus of 20,000 documents and a small proportion of relevant documents (<0.1%), both techniques outperformed a conventional keyword search on a recall-based information retrieval (IR) task. These context-based techniques were associated with a reduction in the number of searches conducted, an increase in users’ precision and, to a lesser extent, an increase in recall. This improvement was strongest when the ranking was based on document, rather than sentence, context. Individuals were more effective on the IR task when the lists returned by the techniques were ranked better. User performance on the task also correlated with achievement on a generalized IQ test but not on a linguistic ability test.

Abstract This article compares search effectiveness when using query‐based Internet search (via the Google search engine), directory‐based search (via Yahoo), and phrase‐based query reformulation‐assisted search (via the Hyperindex browser) by means of a controlled, user‐based experimental study. The focus was to evaluate aspects of the search process. Cognitive load was measured using a secondary digit‐monitoring task to quantify the effort of the user in various search states; independent relevance judgements were employed to gauge the quality of the documents accessed during the search process and time was monitored as a function of search state. Results indicated directory‐based search does not offer increased relevance over the query‐based search (with or without query formulation assistance), and also takes longer. Query reformulation does significantly improve the relevance of the documents through which the user must trawl, particularly when the formulation of query terms is more difficult. However, the improvement in document relevance comes at the cost of increased search time, although this difference is quite small when the search is self‐terminated. In addition, the advantage of the query reformulation seems to occur as a consequence of providing more discriminating terms rather than by increasing the length of queries.

This article compares search effectiveness when using query-based Internet search (via the Google search engine), directory-based search (via Yahoo) and phrase-based query reformulation assisted search (via the Hyperindex browser) by means of a controlled, user-based experimental study. The focus was to evaluate aspects of the search process. Cognitive load was measured using a secondary digit-monitoring task to quantify the effort of the user in various search states; independent relevance judgements were employed to gauge the quality of the documents accessed during the search process. Time was monitored in various search states. Results indicated the directory-based search does not offer increased relevance over the query-based search (with or without query formulation assistance), and also takes longer. Query reformulation does significantly improve the relevance of the documents through which the user must trawl versus standard query-based internet search. However, the improvement in document relevance comes at the cost of increased search time and increased cognitive load.