本論文は，電子掲示板の書き込みなどによるサイバー犯罪を想定し，その犯人性立証の一手法として，多変量データ解析を用いた計量的文体分析を提案するもので，実際に犯人性の立証が困難であったと思われるいわゆる｢パソコン遠隔操作事件｣に関する著者の識別を試みた．分析の際は，疑問文章(｢パソコン遠隔操作事件｣の９事件の文章)，対照文章(｢パソコン遠隔操作事件｣の真犯人であったＫ氏が過去に敢行し，自供した通称｢のまねこ事件｣関連の５つの文章)，無関係文章(Ｋ氏と性別年代が同じ30代男性10名のブログ文章と異なる４つの事件における文章)を対象に，①非自立語の使用率，②品詞のtrigram，③助詞のbigram，④文字のbigramに着目し，階層的クラスター分析を実施した．その結果によると，｢パソコン遠隔操作事件｣の一連の文章と｢のまねこ事件｣の一連の文章は，同一人が記載したものである可能性を示唆した．

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  The effectiveness of identifying the author of an illegal document by using text mining was investigated. The suspected writing evaluated in this study was a claim of responsibility written by a 14-year-old boy, which stated that he committed the “Kobe child murders” in 1997. It was compared with control writings including confessions, and an essay that we knew were written by the same boy, as well as with irrelevant materials including various essays written by five junior high school students, and claims of responsibility in four past criminal cases. First, the writings in each document were digitalized and converted to text files. Then, the relative frequencies of bigram of letters, bigram of part-of-speech taggers, sentence lengths of each document, and rate of using Kanji, Hiragana, and Katakana were calculated. Results of sammon multi-dimensional scaling and hierarchical cluster analysis indicated that the text in the suspected writing was arranged identically or similarly to groups of texts in control materials, where they were arranged differently from groups of texts in irrelevant materials. In a separate analysis, the suspected writing was substituted with a document written by a different offender and we conducted the identical procedure described above. Results demonstrated that texts in the suspected writing were in a different form control and irrelevant texts. These results indicated the effectiveness of identifying an author by using text mining when examining forensic documents.

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