  We feel happy when web-browsing operations provide us with necessary
information; otherwise, we feel bitter. How to measure this happiness (or
bitterness)? How does the profile of happiness grow and decay during the course
of web-browsing? We propose a probabilistic framework that models evolution of
user satisfaction, on top of his/her continuous frustration at not finding the
required information. It is found that the cumulative satisfaction profile of a
web-searching individual can be modeled effectively as the sum of random number
of random terms, where each term is mutually independent random variable,
originating from 'memoryless' Poisson flow. Evolution of satisfaction over the
entire time interval of user's browsing was modeled with auto-correlation
analysis. A utilitarian marker, magnitude of greater than unity of which
describe happy web-searching operations; and an empirical limit that connects
user's satisfaction with his frustration level - are proposed too. Presence of
pertinent information in the very first page of a web-site and magnitude of the
decay parameter of user satisfaction (frustration, irritation etc.), are found
to be two key aspects that dominate web-browser's psychology. The proposed
model employed different combination of decay parameter, searching time and
number of helpful web-sites. Obtained results are found to match the results
from three real-life case-studies.
