Authorship Attribution Analysis of Thai Online Messages
| Title | Authorship Attribution Analysis of Thai Online Messages |
| Publication Type | Conference Paper |
| Year of Publication | 2014 |
| Authors | Marukatat, R., Somkiadcharoen, R., Nalintasnai, R., Aramboonpong, T. |
| Conference Name | Information Science and Applications (ICISA), 2014 International Conference on |
| Date Published | May |
| Keywords | Accuracy, author identification, authorship attribution analysis, C4.5 decision tree, Decision trees, Kernel, natural language processing, support vector machine, Support vector machines, SVM, Thai online messages, Training, Training data, Writing, writing attributes |
| Abstract | This paper presents a framework to identify the authors of Thai online messages. The identification is based on 53 writing attributes and the selected algorithms are support vector machine (SVM) and C4.5 decision tree. Experimental results indicate that the overall accuracies achieved by the SVM and the C4.5 were 79% and 75%, respectively. This difference was not statistically significant (at 95% confidence interval). As for the performance of identifying individual authors, in some cases the SVM was clearly better than the C4.5. But there were also other cases where both of them could not distinguish one author from another. |
| DOI | 10.1109/ICISA.2014.6847369 |
| Citation Key | 6847369 |