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The present study investigates the word formation process of lexical blending in the context of written US web news between January 2010–March 2018. The study has two interrelated aims. First, it aims to develop a transparent, rigid, and replicable method of data collection. This is motivated by a lack of systematicity of data collection procedures in previous research. Second, it aims to identify the characteristics of the retrieved blends; both generally and with a special focus on how ambiguity is realized. The data were collected from an offline version of the NOW corpus (News On the Web). A strict algorithm was devised to organize the data and to identify lexical blends among a large body of systematically collected word forms. Both automatic and manual procedures were employed in these tasks. The study is conducted within the framework of Cognitive Linguistics (CL). Semantic analysis is foregrounded in CL and language is considered perspectival, dynamic, non-autonomous, and experience-based. Furthermore, a Langackerian view on meaning is adopted in that symbolic potential is acknowledged in all resources and manifestations of language. Categorization is approached in accordance with the tenets of prototype theory, which acknowledges fuzzy category boundaries and gradual distribution of attributes.

The results of the study show that the data collection methodology is quantitatively robust, which offers the possibility to generalize the observations within the context of the chosen limitations. Consequently, the developed methodology may also be applied in future investigations. Second, quantitative analyses validate some previous assumptions about grammatical functions, semantics, and seriality in blending. Third, a set of qualitative characteristics are identified in the collected set of blends, which offers a comprehensive approach to describing blend formation in the given context. The characteristics structural profiling and domain proximity are suggested as prominent aspects of blend formation. Structural profiling is marked by prominent structural attributes such as similarity of source words and intricate patterns of amalgamation, but figurative strategies are also foregrounded. Domain proximity is described in terms of semantic similarity between the source words and an iconic relation between the fusion of structure and the fusion of concepts. The notion of pseudomorphemic transfer is used to capture blends that fall within the operational definition of the study but also seem to be connected to other morphological processes through the instantiation of morphological schemata. Blends clustered in series based on recycled truncated segments are revisited from a qualitative perspective, and it is claimed that the process of morphemization is likely influenced by the degree of morpheme-like character of a serially distributed segment. Furthermore, four types of ambiguity are identified in the blend data; truncation ambiguity, mode ambiguity, source word ambiguity, and covert source ambiguity. On the basis of the observed impact of ambiguity, it is suggested that the construal of meaning in lexical blending makes use of multistability, which is a perceptual phenomenon observed in, for instance, binocular rivalry. Taken together, the results constitute a background for suggesting a model of categorization divided into two levels of organization. This model of categorization is called the dual model of blend classification.

The multifaceted and intermediary nature of lexical blending has been discussed from various theoretical perspectives in the last decades [Kubozono 1990; Kelly 1998; Dressler 2000; Kemmer2003; Gries 2006; Fandrych 2008]. Corpus linguistic studies have contributed to a growing body of empirical data demonstrating significant patterns of blend formation [e.g. Gries 2004b, 2006;Beliaeva 2014]. These more recent findings are particularly important as they illustrate that lexical blending is not as irregular and unsystematic as it has often been assumed in the past [Lehrer 1996; Kelly 1998; Kemmer 2003; López Rúa 2004; Beliaeva 2014]. Because blends are often short-lived [Cannon 1986; Lehrer 1996] and informal [Bauer 1983; López Rúa 2010; Bauer 2012], making predictions about their nature is a complex task. Systematic analysis involves therefore a number of challenges. One such challenge is how to detect and collect these unspecified and untagged lexical items in a corpus. It is a well-known fact that conventional dictionaries are poor sources [Cannon 1986], and alternative methodologies are therefore required. Another challenge is how to ensure that the collected data is representative of all lexical blends within a selected set of limitations. Besides addressing these challenges, semantic aspects of ambiguity were investigated from a Cognitive Linguistics (CL) perspective [Geeraerts 2006a]. The patterns of ambiguity in the data are explained as instantiations of multistable perception, which is understood as a phenomenon in which “our perceptual system fails to produce a stable unambiguous percept” [Kornmeier et al. 2009: 138]. From a linguistic perspective, this means that aspects such as phonology, orthography, and semantics constitute variables holding a potential for functionally employed lexical ambiguity [Renner 2015]. At various stages, the study employed both automated processes and manual analyses, which means that workload limitations applied to the scope of the data. A central aim of the study was, however, to develop systematic approaches to the collection of lexical blends, precisely because it is considered necessary in the development of blend research in general.

The multifaceted and intermediary nature of lexical blending has been discussed from various theoretical perspectives in the last decades [Kubozono 1990; Kelly 1998; Dressler 2000; Kemmer 2003; Gries 2006; Fandrych 2008]. Corpus linguistic studies have contributed to a growing body of empirical data demonstrating significant patterns of blend formation [e.g. Gries 2004b, 2006; Beliaeva 2014]. These more recent findings are particularly important as they illustrate that lexical blending is not as irregular and unsystematic as it has often been assumed in the past [Lehrer 1996; Kelly 1998; Kemmer 2003; López Rúa 2004; Beliaeva 2014]. Because blends are often short-lived [Cannon 1986; Lehrer 1996] and informal [Bauer 1983; López Rúa 2010; Bauer 2012], making predictions about their nature is a complex task. Systematic analysis involves therefore a number of challenges. One such challenge is how to detect and collect these unspecified and untagged lexical items in a corpus. It is a well-known fact that conventional dictionaries are poor sources [Cannon 1986], and alternative methodologies are therefore required. Another challenge is how to ensure that the collected data is representative of all lexical blends within a selected set of limitations. Besides addressing these challenges, semantic aspects of ambiguity were investigated from a Cognitive Linguistics (CL) perspective [Geeraerts 2006a]. The patterns of ambiguity in the data are explained as instantiations of multistable perception, which is understood as a phenomenon in which “our perceptual system fails to produce a stable unambiguous percept” [Kornmeier et al. 2009: 138]. From a linguistic perspective, this means that aspects such as phonology, orthography, and semantics constitute variables holding a potential for functionally employed lexical ambiguity [Renner 2015]. At various stages, the study employed both automated processes and manual analyses, which means that workload limitations applied to the scope of the data. A central aim of the study was, however, to develop systematic approaches to the collection of lexical blends, precisely because it is considered necessary in the development of blend research in general.

The complex characteristics of lexical blending have long troubled mainstream word formation research to the extent that it has typically been considered a peripheral issue in linguistics. In recent years this has begun to change, and there is currently a growing body of evidence uncovering the intriguing nature of this word formation process. In the present study, underlying principles and usage-based aspects of lexical blends were examined. Analyses of derivatives of three matrix words, republican, liberal, and vegetarian, revealed the impact of three cognitive constraints on the use of lexical blends: schema transfer effects, neighborhood effects, and effects of the influence from morphological lexicalization. The first constraint fueled blend formation, while the other two displayed a hampering effect on the use of lexical blending. Furthermore, a study of the word class distribution in the datasets showed that there were significant differences in the grammar of lexical blending and compounding, respectively.