{'fraction_non_alphanumeric': 0.017027863777089782, 'fraction_numerical': 0.0030959752321981426, 'mean_word_length': 5.53030303030303, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Response dynamics: A new window on the decision process

The history of judgment and decision making is defined by a trend toward increasingly nuanced explanations of the decision making process. Recently, process models have become incredibly sophisticated, yet the tools available to directly test these models have not kept pace. These increasingly complex process models require increasingly complex process data by which they can be adequately tested. We propose a new class of data collection that will facilitate evaluation of sophisticated process models. Tracking mouse paths during a continuous response provides an implicit measure of the growth of preference that produces a choice---rather than the current practice of recording just the button press that indicates that choice itself. Recent research in cognitive science (Spivey & Dale, 2006) has shown that cognitive processing can be revealed in these dynamic motor responses. Unlike current process methodologies, these response dynamics studies can demonstrate continuous competition between choice options and even online preference reversals. Here, in order to demonstrate the mechanics and utility of the methodology, we present an example response dynamics experiment utilizing a common multi-alternative decision task.