In recent years, automatic or semiautomatic processing and analysis systems for a large amount of social listening data have been introduced and used in many industries. Honda Motor Co., Ltd. is also collecting and analyzing voice of customers from much type of media such as SNS using automatic Social Listening System. And verifying whether corporate images and brands are appropriately communicated or not every day. This verification is also used to find symptoms of risk that may be recalled. On the other hand, we found that there were many copied sentences which were delivered from us to society in collected information as voice and opinion of customers. In this case, if these collected sentences are automatically processed as voice of customers using a normal language processing algorithm, we should have a risk to get excessively more positive result than actual. This is because the information delivered from the company like announcement of a new product etc., always includes many positive expressions. And it has been confirmed that the distributor's advertisement and a large amount of retweets follows it, also causes the same risk for the same reasons. It's hard to say that we are correctly measuring the voice of customers. Based on the above situations, in this paper, firstly, we named the phenomenon as "Echo Phenomenon", which incorrectly recognizes delivered information from us as voice of customers. And present it as a problem. Secondly, we propose a simple method to avoid this Echo Phenomenon problem without damaging useful information as much as possible, and show examples of application and its effect.
Sakamoto, D., Uchida, R., & Tsuda, K. (2017). Problem Presentation of Echo Phenomenon on Social Listening and Proposal of Avoidance Method for It. In Procedia Computer Science (Vol. 112, pp. 1412–1419). Elsevier B.V. https://doi.org/10.1016/j.procs.2017.08.070