The approach taken on how the mental lexicon is organized not only frames individual investigations within those approaches’ certain implications and limitations, but also directs the discussion between researchers at large. Of the original selected literature containing 100 items, network-based approaches comprise 36 items; this loosely suggests that approximately one-third of research pertaining to the mental lexicon employs networks methodologically. As the network metaphor can sometimes seem ubiquitous, it is imperative to distinguish and discriminate between the numerous usages of this commonly used word.
Three broad types of networks have been identified in the data, as illustrated in , namely: simple, connectionist and small-world scale-free complex networks; these types of networks are represented as 22.2% (n = 8), 50% (n = 18) and 27.8% (n = 10) of the selected literature, respectively. These network types have discernible differences which relate to their parameters and affect their implications. It also must be noted that the differences between these network types are not solely mathematical in nature; the differences are represented also in variation of scope and how their findings can be implicated into our understanding of the mental lexicon.
While simple and connectionist networks constitute a majority of the selected literature, the historical lens of this systematic review notes that they have in some regard resulted in today’s research on modern interdisciplinary complex networks. Due to the more encompassing and holistic nature of complex networks, as well as their greater potential implications, these networks will be presented in different sections. In an attempt to expiate on our third research aim, Section 4
of this review will give particular emphasis on future research and resulting implications as it relates to complex networks.
Another manner in which complex networks stand apart from their predecessors is their fluent mix of microscopic, mesoscopic and macroscopic approaches. These different scales in network scope play a major role in the consequences and implications of what can be learned about linguistic behavior in the mental lexicon. The macroscopic approach sets the experimental boundaries on a large scale in attempt to observe over-arching, linguistic behavior at the expense of exploring focused, specific linguistic phenomena. This approach may be seen in many connectionist networks, including Boolean networks (Meara 2006
), which explore questions over the selective or non-selective nature of the multilingual mental lexicon. Conversely, the microscopic approach explores the specific differences in behavior in the mental lexicon which can be analyzed on a smaller basis, such as on the level of individual words, morphemes, or sounds; this approach may be employed in studies such as those exploring the priming effects of specific characteristics of vocabulary information, such as rhyme or specific morphological features. Mesoscopic approaches find a space between the large and small scales of the beforementioned approaches. Complex networks are unique amongst the three types of explored networks in this review, as they fluidly offer a portrait of the organizational features of the mental lexicon incorporating each of the three scales in scope.
An example of this would be in Vitevitch et al.
), where links within the mental lexicon are explored as it relates to phonetic differences between words, while the patterns found in the network at large are compared to those found in other networks which incorporate different linguistic perspectives, such as semantics or morphosyntactic information.
Relating to the mechanical aspects of networks in the mental lexicon, it is important to acknowledge and remember that networks reflect the structure of linked items within the lexicon, and therefore most networked systems require an attached linguistic approach or perspective to link the nodes. In other words, certain networks postulate links between nodes by way of phonetic similarities (Vitevitch 2008
), word association data (Wilks and Meara 2002
), or other discernible properties of language which can be used to organize the lexicon, such as word frequency or semantic categories. In most of the networks in the selected literature, nodes represent words, while the links between nodes represent the linguistic perspective(s) which bind the words within the mental lexicon.
The article has been published on 10.3390/languages5010001