Identification of Most Frequently Occurring Lexis in Information Technology Products-Advertising Unsolicited Bulk E-Mails

E-mail has become an important means of electronic communication but the viability of its usage is marred by Unsolicited Bulk E-mail (UBE) messages. UBE consists of many types like pornographic, virus infected and ‘cry-for-help’ messages as well as fake and fraudulent offers for jobs, winnings and medicines. UBE poses technical and socioeconomic challenges to usage of e-mails. To meet this challenge and combat this menace, we need to understand UBE. Towards this end, the current paper presents a content-based textual analysis of more than 2,200 UBEs which aim at advertising Information Technology (IT) products like printers, toners and software. Technically, this is an application of text parsing and tokenization for an unstructured textual document, and we approach it using Bag of Words (BOW) and Vector Space Document Model (VSDM) techniques. We have attempted to identify the most frequently occurring lexis in the IT products-advertising UBE documents. The analysis of such top 100 lexis is also presented. We exhibit the relationship between occurrence of a word from the identified lexis-set in the given UBE and the probability that the given UBE will be an IT products-advertising one. To the best of our knowledge and survey of related literature, this is the first formal attempt at identification of most frequently occurring lexis in hardware and software products-advertising UBE by its textual analysis. Finally, this is a sincere attempt to bring about alertness against and mitigate the threat of such luring but fake UBE.