Calculating the information content of an information process for a domain expert using Shannon's mathematical theory of communication: a preliminary analysis

Abstract The problem addressed in this article is to use Bertram Brookes' ‘fundamental equation’ as a starting off-point for a conceptual exercise whose purpose is to set out a method for calculating the information content of an information process. The knowledge structure variables in the Brookes' equation are first operationalized, following principles set out in Claude Shannon's mathematical theory of communication. The set of ‘a priori’ alternatives and the a priori probabilities assigned to each member of the set by the person undergoing the information process is the operational definition of the variable ‘K[S]’ from the ‘fundamental equation,’ which represent the person's knowledge structure ‘before’ the information process takes place. The set of ‘a posteriori’ alternatives and the revised probabilities assigned to each member of the set by the person undergoing the information process is the operational definition of the Brookes' variable ‘K[S + ΔS],’ which is the person's knowledge structure ‘after’ the information process takes place. To illustrate how the variables can be determined, an example of a information process is used from a recent real-life archeological discovery.

[1]  E. J. O'Brien,et al.  Elaborative inferencing as an active or passive process. , 1990 .

[2]  Charles Cole.  Shannon revisited: Information in terms of uncertainty , 1993 .

[3]  Michael K. Buckland,et al.  Information as Thing , 1991 .

[4]  Peter Ingwersen,et al.  Information Retrieval Interaction , 1992 .

[5]  H. Kucera,et al.  Computational analysis of present-day American English , 1967 .

[6]  Jean Tague-Sutcliffe,et al.  Measuring information : an information services perspective , 1995 .

[7]  A. Tversky,et al.  Extensional versus intuitive reasoning: the conjunction fallacy in probability judgment , 1983 .

[8]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[9]  F. Machlup,et al.  The Study of Information: Interdisciplinary Messages , 1984 .

[10]  Charles Cole.  Operationalizing the notion of information as a subjective construct , 1994 .

[11]  D. Swinney.  Lexical access during sentence comprehension: (Re)consideration of context effects , 1979 .

[12]  I. Good.  Good Thinking: The Foundations of Probability and Its Applications , 1983 .

[13]  Michel J. Menou,et al.  The Impact of Information - II. Concepts of Information and Its Value , 1995, Inf. Process. Manag..

[14]  Daniel Kahneman,et al.  Availability: A heuristic for judging frequency and probability , 1973 .

[15]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[16]  M. C. Yovits,et al.  A Semiotic Framework for Information Science Leading to the Development of a Quantitative Measure of Information. , 1974 .

[17]  C. Cole.  Information Acquisition in History Ph.d. Students: Inferencing and the Formation of Knowledge Structures , 1998, The Library Quarterly.

[18]  B. Dervin,et al.  Information needs and uses. , 1986 .

[19]  Anthony Debons,et al.  Information Science: An Integrated View , 1988 .

[20]  B. C. Brookes.  The foundations of information science , 1980 .

[21]  Thomas A. Schreiber,et al.  Processing implicit and explicit representations. , 1992, Psychological review.

[22]  W. Kintsch,et al.  Context effects in word identification , 1985 .

[23]  Harry Bruce.  A cognitive view of the situational dynamism of user-centered relevance estimation , 1994 .

[24]  T. Fine.  Theories of Probability: An Examination of Foundations , 1973 .

[25]  B. C. Brookes.  The foundations of information science. Part I. Philosophical aspects , 1980 .

[26]  Bertram C. Brookes.  Measurement in information science: Objective and subjective metrical space , 1980, J. Am. Soc. Inf. Sci..

[27]  W. Kintsch,et al.  Strategies of discourse comprehension , 1983 .

[28]  Broadbent De.  Word-frequency effect and response bias. , 1967 .

[29]  R. Collingwood,et al.  The Idea of History. , 1947 .

[30]  Clinton R. Foulk,et al.  Information flow and analysis: Theory, simulation, and experiments. I. Basic theoretical and conceptual development , 1981, J. Am. Soc. Inf. Sci..

[31]  Peter Ingwersen,et al.  Cognitive Perspectives of Information Retrieval Interaction: Elements of a Cognitive IR Theory , 1996, J. Documentation.

[32]  B. C. Brookes.  ROBERT FAIRTHORNE AND THE SCOPE OF INFORMATION SCIENCE , 1974 .

[33]  Charles Cole,et al.  Information as Process: The Difference Between Corroborating Evidence and 'Information' in Humanistic Research Domains , 1997, Inf. Process. Manag..

[34]  M. D. Mey,et al.  The Cognitive Paradigm: Cognitive Science, a Newly Explored Approach to the Study of Cognition Applied in an Analysis of Science and Scientific Knowledge , 1982 .

[35]  Walter Kintsch,et al.  Sentence memory: A theoretical analysis ☆ , 1990 .

[36]  Robert M. Kleyle,et al.  The average decision maker and its properties utilizing the generalized information system model , 1993 .

[37]  J. Fodor.  The Modularity of mind. An essay on faculty psychology , 1986 .

[38]  A. Tversky,et al.  Subjective Probability: A Judgment of Representativeness , 1972 .