%0 Journal Article %1 finn_source_1984 %A Finn, Seth %A Roberts, Donald F. %D 1984 %J Communication Research %K classic-work-treatment communication-theory engineering information-theory intellectual internalist united-states %P 453--476 %R 10.1177/009365084011004001 %T Source, Destination, and Entropy: Reassessing the Role of Information Theory in Communication Research %V 11 %X Although Shannon and Weaver's The Mathematical Theory of Communication has had a profound impact on the development of communication research, few scholars have adapted Shannon's concepts to their research questions. The authors argue that the failure to recognize the difference between the two fundamental orientations in Shannon's theory—the relationship between source and destination and the technical characteristics of transmission channels—has retarded the use of Shannon's concepts, especially his measure of information. Taking care to differentiate between these two aspects of information theory, the authors review the small body of empirical research inspired by Shannon's theory. They find that Shannon's entropy measure is especially useful in the study of human systems because it permits researchers to analyze categorical data using quantitative statistical tools.

@article{finn_source_1984, abstract = {Although Shannon and Weaver's The Mathematical Theory of Communication has had a profound impact on the development of communication research, few scholars have adapted Shannon's concepts to their research questions. The authors argue that the failure to recognize the difference between the two fundamental orientations in Shannon's theory\textemdash{}the relationship between source and destination and the technical characteristics of transmission channels\textemdash{}has retarded the use of Shannon's concepts, especially his measure of information. Taking care to differentiate between these two aspects of information theory, the authors review the small body of empirical research inspired by Shannon's theory. They find that Shannon's entropy measure is especially useful in the study of human systems because it permits researchers to analyze categorical data using quantitative statistical tools.}, added-at = {2019-08-29T01:56:31.000+0200}, author = {Finn, Seth and Roberts, Donald F.}, biburl = {https://www.bibsonomy.org/bibtex/28e3bdcf1a57fb84ce7e659c127edcfec/jpooley}, doi = {10.1177/009365084011004001}, interhash = {51db0bbe3bb6e172022dc7bb1b732d28}, intrahash = {8e3bdcf1a57fb84ce7e659c127edcfec}, journal = {Communication Research}, keywords = {classic-work-treatment communication-theory engineering information-theory intellectual internalist united-states}, pages = {453--476}, timestamp = {2019-08-29T01:56:31.000+0200}, title = {Source, {{Destination}}, and {{Entropy}}: {{Reassessing}} the {{Role}} of {{Information Theory}} in {{Communication Research}}}, volume = 11, year = 1984 }