Measuring Individual Differences in Word Recognition: The Role of Individual Lexical Behaviors

Measuring Individual Differences in Word Recognition: The Role of Individual Lexical Behaviors ��� Hsin-Ni Lin �������������� Department of English, Linguistics Division National Taiwan Normal University hnlin98@std.ntnu.edu.tw ��� Shu-Kai Hsieh ��������� Graduate Institute of Linguistics National Taiwan University shukaihsieh@ntu.edu.tw ��� Shiao-Hui Chan �������������� Department of English, Linguistics Division National Taiwan Normal University shiaohui@ntnu.edu.tw Abstract This study adopts a corpus-based computational linguistic approach to measure individual differences (IDs) in visual word recognition. Word recognition has been a cardinal issue in the field of psycholinguistics. Previous studies examined the IDs by resorting to test-based or questionnaire-based measures. Those measures, however, confined the research within the scope where they can evaluate. To extend the research to approximate to IDs in real life, the present study undertakes the issue from the observations of experiment participants’ daily-life lexical behaviors. Based on participants’ Facebook posts, two types of personal lexical behaviors are computed, including the frequency index of personal word usage and personal word frequency. It is investigated that to what extent each of them accounts for participants’ variances in Chinese word recognition. The data analyses are carried out by mixed-effects models, which can precisely estimate by-subject differences. Results showed that the effects of personal word frequency reached significance; participants responded themselves more rapidly when encountering more frequently used words. People with lower frequency indices of personal word usage had a lower accuracy rates than others, which was contrary to our prediction. Comparison and discussion of the results also reveal methodology issues that can provide noteworthy suggestions for future research on measuring personal lexical behaviors. Proceedings of the Twenty-Fourth Conference on Computational Linguistics and Speech Processing (ROCLING 2012) 61 Keywords: individual differences, lexical behaviors, word recognition, computational linguistic approach, naturalistic data 1. Introduction In the field of psycholinguistics, a major research interest is to investigate how people recognize written words or access the corresponding word representations stored in their mental lexicon. Psycholinguists usually undertake the investigation starting from isolated words since less factors are involved, compared to words within sentences. Therefore, research on the isolated word recognition is fundamental for understanding how lexical access takes places. In general, the term ‘visual word recognition’ is used to simply address the recognition of isolated written words. Research of word recognition traditionally have concentrated on how characteristics of words per se (e.g. word length, word frequency, or neighborhood size) affected the procedure of recognition [1] [2] [3] [4] [5], taking the discrepancies between participants’ performance as merely statistical deviation. Recently, however, there has been a growing interest in the individual differences (IDs, henceforth) of experiment participants. Results of the ID studies showed that the issue was noteworthy because personal experiences and knowledge of words (e.g. print-exposure experience [6] [7], reading skills [8], or vocabulary knowledge [9] [10] [11]) accounted for systematic variances between participants in word recognition. Even when participants were homogeneous in their educational level, their IDs sufficiently resulted in distinct performance in word recognition. Furthermore, [8] provided compelling evidence that conflicting results of regularity effects1 in the literature …

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