Investigating the semantic representation of Chinese emotion words with co-occurrence data and self-organizing maps neural networks


Regarding to the investigation of the representations of words, previous researchers often ask participants to rate the similarities between emotion words (Barrett, 2004; Cheng, Cheng, Cho, & Chen, 2013; Romney, Moore, & Rusch, 1997), or to give the scores upon certain psychological dimensions (e.g. valence, arousal)(Bradley & Lang, 1999; Cho, Chen, & Cheng, 2013; Morgan & Heise, 1988). These direct similarity-based or anchor-based ratings indeed emerge categorical properties of emotion words according to existing theoretical postulations. However, it is unknown whether there are implicit dimensions embedded within their semantic representations. Furthermore, it is also important to know how the semantic representation of emotion words would present their meaning relationships in terms of considering a multiple word-meaning pool.