Abstract
Financial discussion boards (FDBs) or financial forums on the Internet allow investors and traders to interact with each other in the form of posted comments. The purpose of such FDBs allows investors and traders to exchange financial knowledge. Unfortunately, not all posted content on FDBs is truthful. While there are genuine investors and traders on FDBs, deceivers make use of such publicly accessible share price based FDBs to carry out financial crimes by tricking novice investors into buying the fraudulently promoted stocks. Generally, Internet forums rely on default spam filtering tools like Akismet. However, Akismet does not moderate the meaning of a posted content. Such moderation relies on continuous manual tasks performed by human moderators, but it is expensive and time consuming to perform. Furthermore, no relevant authorities are actively monitoring and handling potential financial crimes on FDBs due to the lack of moderation tools. This paper introduces a novel methodology, namely, forward analysis, employed in an Information Extraction (IE) system, namely, FDBs Miner (FDBM). This methodology aims to highlight potentially irregular activities on FDBs by taking both comments and share prices into account. The IE prototype system will first extract the public comments and per minute share prices from FDBs for the selected listed companies on London Stock Exchange (LSE). Then, in the forward analysis process, the comments are flagged using a predefined Pump and Dump financial crime related keyword template. By only flagging the comments against the keyword template, results indicate that 9.82% of the comments are highlighted as potentially irregular. Realistically, it is difficult to continuously read and moderate the massive amount of daily posted comments on FDBs. The incorporation of the share price movements can help to categorise the flagged comments into different price hike thresholds. This allows related investigators to investigate the flagged comments based on priorities depending on the risk levels as it can possibly reveal real Pump and Dump crimes on FDBs.
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Lee, P.S., Owda, M., Crockett, K. (2019). The Detection of Fraud Activities on the Stock Market Through Forward Analysis Methodology of Financial Discussion Boards. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, vol 887. Springer, Cham. https://doi.org/10.1007/978-3-030-03405-4_14
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