Entropy, originally a concept from thermodynamics, refers to the amount of energy in a system that is no longer available for mechanical work. However, it has also found applications in communication theory, where it represents a numerical measure of the uncertainty of an outcome. In simpler terms, entropy can be used to measure the extent of disorder in information.
When we apply this concept to the vast amount of information available on the Web 2.0, it becomes apparent that seeking specific information within this vast sea of data is like searching for a single drop of water in an ocean with extremely high entropy. The sheer magnitude and disorder of information on the internet make it challenging to locate and evaluate reliable sources.
In the context of tagging, it becomes evident that tagging is an individual behavior, where users assign labels or tags to information based on their own understanding and categorization. However, social tagging takes this process a step further by crowdsourcing the tagging process (Chi & Mytkowicz, 2007). By allowing users to collectively tag information, social tagging harnesses the collective intelligence of the crowd to organize and categorize content.
Interestingly, tagging can also be seen as a computer behavior in the field of computer science. Tagging in this context can be regarded as a form of categorization that helps to combat the inherent entropy of information (Chi & Mytkowicz, 2008). By assigning relevant tags to data, computers can enhance the organization and retrieval of information, making it more accessible and less disorderly.
Overall, the concept of entropy provides a valuable lens through which we can understand the challenges of seeking and organizing information in the context of Web 2.0. By recognizing the high entropy of the digital landscape, we can appreciate the importance of individual and social tagging behaviors, as well as the role of computers in mitigating information disorder through categorization.
Regerences
Chi, E. H., & Mytkowicz, T. (2007, April). Understanding navigability of social tagging systems. In Proceedings of CHI (Vol. 7).
Chi, E. H., & Mytkowicz, T. (2008, June). Understanding the efficiency of social tagging systems using information theory. In Proceedings of the nineteenth ACM conference on Hypertext and hypermedia (pp. 81-88).