The Effect of Incidental Semantic Activation on Hypothesis Generation: Exclusive vs Compatible Hypotheses

우연적 의미 활성화가 가설 생성에 미치는 영향: 가설 유형에 따른 차이

  • Lee, Younha (Interdisciplinary Program in Cognitive Science, Psychology, Seoul National University) ;
  • Park, Jooyong (Interdisciplinary Program in Cognitive Science, Psychology, Seoul National University)
  • 이윤하 (서울대학교 인지과학 협동과정, 심리학과) ;
  • 박주용 (서울대학교 인지과학 협동과정, 심리학과)
  • Received : 2015.02.23
  • Accepted : 2015.06.22
  • Published : 2015.06.30


Previous studies on the effect of incidental semantic priming on judgment, have focused mainly on mutually exclusive hypotheses. However, the present study explored whether incidental semantic activation affects diagnostic inference depending on the type of the hypothesis: mutually exclusive hypotheses vs compatible hypotheses. In Experiment 1, in case of mutually exclusive hypotheses, the final hypothesis was selected according to the incidental semantic priming, but there was no difference in the number of generated hypothesis in comparison with the control. However, for compatible hypotheses (i.e., both hypotheses can be true), the semantic priming affected the number of generated hypotheses, but not the selection of the final hypothesis. The same pattern of results was observed even when the cognitive load was increased. In Experiment 2, we found a boundary condition of incidental semantic activation on diagnostic inference. When cues related to each of the hypotheses were presented simultaneously, the incidental semantic effect disappeared. These results suggest that people consider all possible cues when making diagnostic inference in daily life. In light of these findings, further research on hypothesis generation/evaluation should take the type of hypothesis into account.


  1. Agnoli, F. (1991). Development of judgmental heuristics and logical reasoning: Training counteracts the representativeness heuristic. Cognitive Development, 6, 195-217
  2. Alter, A. L. & Oppenheimer, D. M. (2009). Uniting the tribes of fluency to form a metacognitive nation. Personality and Social Psychology Review.
  3. Bassok, M. & Novick, L. R. (2012). Problem solving. Oxford handbook of thinking and reasoning, 413-432.
  4. Dougherty, M. R. & Hunter, J. (2003). Probability judgment and subadditivity: The role of working memory capacity and constraining retrieval. Memory & Cognition, 31(6), 968-982.
  5. Erb, H. P., Bioy, A., & Hilton, D. J. (2002). Choice preferences without inferences: Subconscious priming of risk attitudes. Journal of Behavioral Decision Making, 15(3), 251-262.
  6. Fenton, N. & Neil, M. (2012). Risk assessment and decision analysis with Bayesian networks. CRC Press.
  7. Gilad, D. & Kliger, D. (2008). Priming the Risk Attitudes of Professionals in Financial Decision Making. Review of Finance, 12(3), 567-586.
  8. Ho, J. L. & Keller, L. R. (1994). The effect of inference order and experience-related knowledge on diagnostic conjunction probabilities. Organizational Behavior and Human Decision Processes, 59(1), 51-74.
  9. Josephson, J. R. & Josephson, S. G. (Eds.). (1996). Abductive inference: Computation, philosophy, technology. Cambridge University Press.
  10. Kahneman, D. & Miller, D. T. (1986). Norm theory: comparing reality to its alternatives. Psychological Review, 93, 136-153.
  11. Kahneman, D. (2003). A perspective on judgment and choice: mapping bounded rationality. American psychologist, 58(9), 697.
  12. Kelley, C. M. & Lindsay, D. S. (1993). Remembering mistaken for knowing: Ease of retrieval as a basis for confidence in answers to general knowledge questions. Journal of Memory and Language, 32(1), 1-24.
  13. Kusev, P., van Schaik, P., & Aldrovandi, S. (2012). Preferences induced by accessibility: Evidence from priming. Journal of Neuroscience, Psychology, and Economics, 5(4), 250.
  14. Lange, N. D., Thomas, R. P., Buttaccio, D. R., Illingworth, D. A., & Davelaar, E. J., (2013). Working memory dynamics bias the generation of beliefs: The influence of data presentation rate on hypothesis generation. Psychonomic bulletin and review, 20:171-176.
  15. LeBoeuf, R. A. & Shafir, E. (2003). Deep thoughts and shallow frames: On the susceptibility to framing effects. Journal of Behavioral Decision Making, 16(2), 77-92.
  16. Libby, R. & Frederick, D. M. (1990). Experience and the ability to explain audit findings. Journal of Accounting Research, 348-367.
  17. Libby, R. (1985). Availability and the generation of hypotheses in analytical review. Journal of Accounting Research, 648-667.
  18. Lombrozo, T. (2006). The structure and function of explanations. Trends in cognitive sciences, 10(10), 464-470.
  19. Lombrozo, T. (2007). Simplicity and probability in causal explanation. Cognitive psychology, 55(3), 232-257.
  20. Lombrozo, T. (2012). Explanation and abductive inference. Oxford handbook of thinking and reasoning, 260-276.
  21. Malt, B. C., Ross, B. H., & Murphy, G. L. (1995). Predicting features for members of natural categories when categorization is uncertain. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(3), 646.
  22. McKenzie, C. R. (1998). Taking into account the strength of an alternative hypothesis. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24(3), 771.
  23. Mehlhorn, K., Taatgen, N. A., Lebiere, C., & Krems, J. F. (2011). Memory activation and the availability of explanations in sequential diagnostic reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(6), 1391.
  24. Pennington, N. & Hastie, R. (1988). Explanation-based decision making: Effects of memory structure on judgment. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(3), 521.
  25. Reggia, J. A., Nau, D. S., & Wang, P. Y. (1985). A formal model of diagnostic inference. I. Problem formulation and decomposition. Information Sciences,37(1), 227-256.
  26. Reyes, R. M., Thompson, W. C., & Bower, G. H. (1980). Judgmental biases resulting from differing availabilities of arguments. Journal of Personality and Social Psychology, 39(1), 2.
  27. Ross, L. D., Lepper, M. R., Strack, F., & Steinmetz, J. (1977). Social explanation and social expectation: Effects of real and hypothetical explanations on subjective likelihood. Journal of Personality and Social Psychology, 35(11), 817.
  28. Schwarz, N. (2004). Metacognitive experiences in consumer judgment and decision making. Journal of Consumer Psychology, 14(4), 332-348.
  29. Schwarz, N., Sanna, L. J., Skurnik, I., & Yoon, C. (2007). Metacognitive experiences and the intricacies of setting people straight: Implications for debiasing and public information campaigns. Advances in experimental social psychology, 39, 127.
  30. Shafir, E. & LeBoeuf, R. A. (2002). Rationality. Annual Review of Psychology, 53, 419-517.
  31. Sloman, S. A. (1994). When explanations compete: The role of explanatory coherence on judgements of likelihood. Cognition, 52(1), 1-21.
  32. Smith, S. M. & Levin, I. P. (1996). Need for cognition and choice framing effects. Journal of Behavioral Decision Making, 9(4), 283-290.<283::AID-BDM241>3.0.CO;2-7
  33. Snyder, M. & Swann, W. B. (1978). Hypothesis-testing processes in social interaction. Journal of Personality and Social Psychology, 36(11), 1202.
  34. Sprenger, A. & Dougherty, M. R. (2012). Generating and evaluating options for decision making: the impact of sequentially presented evidence. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38(3), 550.
  35. Strack, F., Schwarz, N., Bless, H., Kubler, A., & Wanke, M. (1993). Awareness of the influence as a determinant of assimilation versus contrast. European Journal of Social Psychology, 23(1), 53-62.
  36. Thagard, P. (1997). Probabilistic Networks and Explanatory Coherence. Automated Abduction: Inference to the best explanation.
  37. Thomas, R. P., Dougherty, M. R., Sprenger, A. M., & Harbison, J. (2008). Diagnostic hypothesis generation and human judgment. Psychological Review,115(1), 155.
  38. Tormala, Z. L., Petty, R. E., & Brinol, P. (2002). Ease of retrieval effects in persuasion: Aself-validation analysis. Personality and Social Psychology Bulletin, 28(12), 1700-1712.
  39. Tsai, C. I., Klayman, J., & Hastie, R. (2008). Effects of amount of information on judgment accuracy and confidence. Organizational Behavior and Human Decision Processes, 107(2), 97-105.
  40. Tseng, I., Moss, J., Cagan, J., & Kotovsky, K. (2008). The role of timing and analogical similarity in the stimulation of idea generation in design. Design Studies, 29(3), 203-221.
  41. Tversky, A. & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive psychology, 5(2), 207-232.
  42. Van Wallendael, L. R. & Hastie, R. (1990). Tracing the footsteps of Sherlock Holmes: Cognitive representations of hypothesis testing. Memory & Cognition,18(3), 240-250.
  43. Weber, E. U., Bockenholt, U., Hilton, D. J., & Wallace, B. (1993). Determinants of diagnostic hypothesis generation: effects of information, base rates, and experience. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19(5), 1151.
  44. Zuckerman, M., Knee, C. R., Hodgins, H. S., & Miyake, K. (1995). Hypothesis confirmation: The joint effect of positive test strategy and acquiescence response set. Journal of Personality and Social Psychology, 68(1), 52.