  The difficulties involved in spelling error detection and correction in a
language have been investigated in this work through the conceptualization of
SpellNet - the 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 among them being that the
probability of making a real word error in a language is propotionate to the
average weighted degree of SpellNet, which is found to be highest for Hindi,
followed by Bengali and English.
