The difficulties involved in spelling error detection and correction in a language
have been investigated in this work through the conceptualization of SpellNet - a
weighted network of words, where edges indicate orthographic proximity between two
words. We construct SpellNets for three languages - Bengali, English and Hindi.
Through appropriate mathematical analysis and/or intuitive justification, we
interpret the different topological metrics of SpellNet from the perspective of the
issues related to spell-checking. We make many interesting observations, the most
significant being that the probability of making a read word error in a language is
proportionate to the average weighted degree of SpellNet, which is found to be
highest for Hindi, followed by Bengali and English.