Experiments on Processing Lexical Blends



Experiments on Processing Lexical Blends*

Adrienne Lehrer and Csaba Veres

University of Arizona University of Bergen

Lexical blends have existed in English for a long time, but in recent years their creation has accelerated greatly, so much so that, at least in the US, it is hard to avoid new ones. Yet mainstream morphologists have treated them as marginal in spite of their increasing popularity. When they appear in context, however, they seem easy to process, so we decided to carry out some experiments to tap into the mechanisms of processing them. In 1997 and 1998 we carried out several experiments on how subjects process lexical blends under time pressure. Although this work was never published, the International Conference on Lexical Blending has provided us with an opportunity to present our results and to suggest ways that we might have continued with our project.

Our goal was to gain some insight into processing through psycholinguistic experiments. There is a large literature on how much speakers of a language decompose complex words, including compounds (the basis of lexical blends), and our hypothesis was that similar decomposition may take place with blends. The work built on earlier work of Lehrer (1996), in which subjects were presented with blends and asked to identify the targets (the two-word compounds underlying the blends) and to provide meanings. There were no time constraints in those studies.

The point of these new experiments was to try to find evidence for rapid, automatic processing in the decomposition of the blends. Thus, while the conscious task of overtly identifying the components of meaning and assigning an interpretation requires time and effort, the process might involve an initial, possibly preconscious stage where candidate words are automatically activated for further consideration. Since these are not reported through conscious introspection, more subtle experimental techniques are required. After establishing some basic properties of timed blend identification, we present two experiments. The first is a variation of the stem completion task and the second a lexical decision task.

1. Timed Responses and Stem Completions

Experiment 1 consisted of two parts: (1) identifying the underlying words in a blend and (2) a stem completion task. The first task that experiment we carried out was basically a replication of Lehrer's earlier experiment with the addition of time constraints. We based our method oon lexical decision tasks although our task was not a lexical decision task but rather a lexical interpretation task..

Experiment 1: First task. Pilot.

Method

Some blends were novel and others not. Subjects were 38 undergraduate students in linguistics courses, and they were given extra credit for their voluntary participation A pilot test was carried out with four subjects who were told that the purpose of the experiment was to identify the target words and interpret the blends. They were given several examples and also had some practice before the experimental stimuli were presented. Subjects sat in front of a computer screen and pushed a foot pedal to bring up an item on the screen. They were told to press the yes button as soon as they could identify and understand the blend, which ended the trial and recorded the elapsed time from the presentation of the blend. Although the apparatus also had a no button, subjects were told not to use it for this experiment. A tape recorder was placed beside the computer, into which subjects spoke the two target words and a gloss which they felt was appropriate for the blend. The four subjects needed a long time to respond, an average time of 2222ms. (Null responses were never included in our calculations.) In addition, the response time was quite variable. We hypothesized that much of the time might involve finding a plausible interpretation of the blend itself, so we eliminated this step from the instructions in the main experiment and told subjects only to identify the target words.

Experiment 1 Identifying the targets.

Subjects were 38 undergraduate students in linguistics courses, and they were given extra credit for their voluntary participation Subjects saw one of two lists of 40 blends with different blends on each list. The purpose of the two lists was for the stem-completion task, described below. Each list each contained four types of blends: word + splinter (oildralic < oil + hydraulic) splinter + word (narcoma < narcotic + coma), two splinters (dramedy < drama + comedy), and complete overlap (slanguage < slang + language). Some blends were novel, such as bombphlet and others not. As before, subjects brought up an item onto the screen by pushing a foot pedal, After pushing the yes button, the computer recorded the time, and the subjects spoke the target words into a microphone.

Table 1 presents the time that subjects took, which was even longer than response times for the pilot. The mean response time for The 21 subjects who saw List 1 and the 17 who saw List 2 required almost three seconds.

Table 1 Response times for identification of y blend targets.

| |Pilot NS = 4 |List 1 NS = 21 |List 2 NS = 17 |

|Mean response time |2222 ms |2986 ms |2994 ms |

|Mean standard deviation |680 ms |828 ms |595 ms |

An ANOVA was carried out to compare the response time for different blend types, but the F value of .69 was not significant.

A conjecture for why reaction times are so long is that speakers automatically wait for an interpretation before responding, so the reaction times overestimate the amount of time it takes simply to recognize the component words Whether the two processes of identifying and then interpreting the two targets are done sequentially, overlapping, or in parallel is something for future research. In the subsequent experiments we tried to find out if the component words were actually available before the response was recorded.

1.1.2 Identifying the targets.

The spoken responses were transcribed and classified as correct. "Correct" responses were determined by their identity to the ads, magazine headings, and brand names which provided the blends we used, or they were conventional items, like infomercial. There were a small number of additional responses which were equally good (as judged by AL). For example, the target words for biologue were biography and dialogue, but biology was classified as plausible. However, when the additional items were added to the "correct" one, the results were not affected much. Table 2 summarizes the results.

Table 2: Percentage correct for each types of blend

| |Word + splinter |Splinter + word |Two splinters |Overlap |

|List 1 | 52% | 50% | 34% | 69% |

|List 2 | 79% | 77% | 54% | 59% |

Subjects who saw List 2 did better than those who saw List 1, and this might beis due to the fact that List 2 was easier. Note that in spite of this, the reaction times did not differ in the previous analysis. Perhaps this is because even though the component words in List 2 were easier to recognize than in List 1, the reaction time is controlled by the time it takes to generate a gloss, as we have already suggested.

There was no attempt to match the two lists, and in retrospect we should have done this to explore more variables. The number of items with complete overlap was small, but the items were easy: On List 1: guestimate, slanguage, and clandestiny. On List 2 were palimony, globaloney, and selectric. Palimony < pal + alimony was easily identified because at the time that word, coined by journalists, was in the news to describe a scandal. The actor Lee Marvin, who had a house in Tucson, had broken up with his partner. She was suing him because she claimed that he gave her a verbal promise to share his wealth as he would a wife in case of separation. She said he had broken his promise.

Experiment 1 Second task 1.2.1 Stem completions and implicit memory

The stem completion task attempted to determine if subjects remembered the parts of the blends, even in the absence of explicit recognition of those parts. That is, can we find evidence for the activation of a lexical item involved in a blend that is never explicitly recognized? The experiment was suggested by work on implicit memory. Graf and Mandler (1982), Graf and Schacter (1985), and Schacter (1987) summarize data showing evidence for two memory systems: implicit memory and explicit memory. Implicit memory is defined by Graf and Schacter (1985: 501) as facilitation on a task "in the absence of conscious recollection," whereas explicit memory is revealed when performance requires conscious recollection of previous experiences.

Graf and Mandler (1982) devised a study-task on memory. Subjects were given a stack of cards with one word on each card. There were two conditions: a semantic one, in which subjects were to decide how much they liked or disliked the words, and a non-semantic one where they subjects had to decide if the letters on one card were similar to those on the previous card. Then all subjects were given a list of stems, three-letter words that could be completed by an English word. Subjects were told to complete the stems with the first word that came to mind (implicit memory instructions). They were then asked to recall as many of the words from the cards as they could (explicit memory). Only those who performed the semantic task could recall some of the words; the other subjects recalled few. However, on the stem completions, subjects from both groups did equally well, and both completed the stems with the words they saw five times as often as a control group which had not seen the words.

Returning to our own experiment, immediately after the computer work was finished, subjects performed the stem completion task. They were given a list of stems, a sequence of two or thee letters that could be the beginning of possible English words. Most stems were three letters; two were used only when three would certainly trigger the target. Half the stems were from blends on List 1 and half from those on List 2. In addition, half of each of these could be the beginning of the first part of the blend and half the beginning of the second. Table 3 gives examples of the stems we used.

Table 3: Examples of stems

|Stem |Blend |Target |

|COM__ |dramedy |comedy |

|BRA__ |branchizing |branch |

|PAM__ |bombphlet |pamphlet |

|DES__ |deskercize |desk |

|INC__ |coaccidental |incidental |

|HUR__ |hurricoon |hurricane |

Subjects were instructed to complete the stem with the first word that came to mind beginning with those letters.

1.2.2 Stem completion results

There were significantly more stem completions based on the blends seen by subjects than chance, where chance was defined by the responses of those who had not seen the blend. (Each group served as the control for the other group.)

Table 4: Stems completions with blend target.

|Saw |List 1 # = 21 |List 2 # = 17 |

|L1 Target |252 |109 |

|L2 Target | 77 |122 |

Х2 = 52 p. < .001

In addition we calculated responses that used a morphologically related word. For example, in the blend successories, < success + accessories, if a subject completed the stem SUC with succeed, that counted as related. However, most related words were plurals of singular nouns or inflectional variants of verbs.

Since 21 subjects saw List 1 and only 17 saw List 2, the numbers in Table 4 are adjusted for a better comparison by multiplying the responses to List 2 by 1.24 to show the percentages in Table 5. As can be seen, subjects who had been primed by seeing a blend on the computer screen were twice as likely to use the underlying constituentthat word to complete a stemet as the unprimed subjects.

Table 5: Percentage of primed and unprimed stem completions.

| |Primed |Unprimed |

| |% |% |

|Target |68 |34 |

|Target + Related |65 |35 |

In retrospect, we should have looked at the various subclasses of responses, especially to seelearn if there were significant differences between stems that could be completed by the first word of the target as opposed to the second word in the target.

1.2.3 Stem completions and identification of targets.

So far, we have shown that stem completions can be used to measure the effects of previously presented items in this task. But the really interesting question is still unanswered. That is, what happens to items that were not

fully processed to the point where subjects could give a coherent gloss? To answer the question we analyzed the oral response of subjects and correlated them with stem completions. Responses were categorized into four classes: (1) subjects identified the target and completed the stem with that word; (2) they identified the word but did not choose it for the stem; (3) they did not identify the word but completed the stem with it anyway,; and (4) they neither identified the word nor completed the stem with it. The fourth class contained a subclass where the subjects misidentified the target word and used that in the stem completion. There were five instances with subjects who saw List 1 in this subclass. Table 6 shows these results.1

Table 6: Correlation of stem completions and correct identification of targets.

| |Identified word |Identified word |Did not identify |Did not identify |

| |and chose for |but did not |word but chose |word or choose |

| |stem |choose for stem |for stem |for stem |

| |No. % |No. % |No. % |No. % |

|Saw List 1 |216 27 |294 37 |64 8 |226 28 |

|Saw List 2 |101 18 |271 50 |28 5 |147 27 |

The relevant case here is the items in the third column, cases where the subjects did not identify the word but used it on the stem completion anyhow. The total number for List 1 is 64, which is 8% of all responses, and for List 2, 28, which is 5% of all responses. Since the numbers are small, we feel these data are preliminary.2

1.3 Familiarity

Finally subjects were given a list of all the blends and asked which ones they had seen or heard before the experiment. Items were divided into those which over half of the responses were correct and those in which fewer than half were correct. Then the items in the first group wereas further divided into those in which over half the subjects reported having seen or heard the blend previously and those who had not. T-tests showed a significant difference in response times for List 1 (p < .01) but not significant for List 2. This mixed result suggests more investigation is needed, but even if there are significant differences, the phenomenon is compatible with two explanations: (1) blends are stored as parsed with pointers to target words, or (2) subjects had previously decomposed them and could do so again, but more quickly than the first time.

Unfortunately we left the project before completing more detailed analyses of our data and/or replicating the experiment by controlling for more variables, such as the frequency and neighbors of the target words. We could have also looked at each subject's protocol, such as familiarity instead of pooling the data. Also in retrospect we did not focus on the interesting category 3 results in which subjects did not identify the targets but chose that word for the stem anyway. Finally, we should have matched the two lists in the ways described at the end of the paper.

Experiment 2. Lexical decisions tasks with masked priming.

The second set of experiments was intended to explore rapid, automatic decomposition. Although the research showing that morphological decomposition for complex words and compounds is mixed, it still suggestsed that we might find evidence for automatic decomposition of blends.

This set of experiments used the lexical decision task with masked priming. In a lexical decision experiment, subjects are presented with a string of letters and they have to decide as quickly as possible whether the letters spell a word in their language or not. They then press a yes or no button, which records the time. Usually half the stimuli are words and the other half nonwords.

One variation uses a prime, which is an item preceding the target item which is either identical to the target or related, either phonologically, morphologically, orthographically or semantically. related. For example, if the target word is operate, then presenting operate again or operation or doctor earlier in the list will speed up a subject's response to operate. Forster (1985) has shown that an identical or related word presented can serve as a prime for up to 10 following words.

A modification is the use of a masked prime, which is a repetition effect that occurs when the same lexical item is accessed twice in rapid succession, usually for a very short time, e.g., 50 milliseconds. This effect is independent of word frequency and word type., Although difficult to detect, a masked prime produces a reliable effect in speeding up the response time for words, but not for nonwords (Forster, 1985).

Our hypothesis was that when words are primed by blends, subjects would correctly respond faster to words than would subjects who were not primed.

Identical primes < Blend primes < Unrelated primes

Fastest Intermediate Slowest

2.1 Method

Three litssets of stimuli were constructed for three groups of subjects (none from the previous experiment). Each listset had a total of 126 randomized items, half of which were words and half nonwords. In each listset of words there were 63 targets: 21 words where the masked prime was a blend and the target was one of the words for the blend, 21 words with identical primes, and 21 words with unrelated primes. In each listset of the 21 blends, 7 consisted of a word followed by a splinter, 7 of a splinter followed by a word, and 7 of two splinters. If the masked prime was a blend, subjects would see the following, one line at a time at the exactly the same place on the computer screen and taking up exactly the same amount of space:

a string of hashatch marks ####### 1000 ms

a masked prime in small letters dynetic 100 ms

a target word in capital letters DYNAMIC 1000 ms

The three lists were counterbalanced, so that all subjects saw the same 63 targets, and each group saw only one of the masked primes. 21 saw an identical prime, 21 saw a blend prime, and 21 saw an unrelated prime.

Condition 1 Condition 2 Condition 3

########## ########## ##########

fruitopia ##fruit## stillborn

##FRUIT## ##FRUIT## ##FRUIT##

The hashtch marks, serving as a forward mask, call attention to the screen and appeared for one second. Since both the primes and targets were long, often 10 letters or more, we used masked primes of 100ms. In cases where the blend contained more or fewer letters, hashtch marks were used so that each line was the same length. Then hatchhash marks were present for all groups. About half the subjects reported that they did not notice anything between the hatchhash marks and the target. Many of the others noticed a flicker but did not realize that they were seeing letters. A few subjects could read short words. Only one subject reported being able to read the primes, and he had the highest error rate (24%) since he was frequently responding to the primes.

All subjects saw the same 63 targets, but each group saw only one of the masked primes.: 21 saw an identical prime, 21 saw a blend prime, and 21 saw an unrelated prime.

Condition 1 Condition 2 Condition 3

########## ########## ##########

fruitopia ##fruit## stillborn

##FRUIT## ##FRUIT## ##FRUIT##

Subjects were 59 undergraduate studentss in linguistics classes who were paid for their time and in some cases given extra credit as well. By pushing a foot pedal, subjects brought up an item on the screen to begin the timing. First the hatchhash marks appeared, followed by the masked prime, then followed by the target, which remained on the screen for one second. A yes and no button were placed on the table at which the subjects were seated. Subjects were to decide as quickly and accurately as possible whether the letters spelled a word and then to press the appropriate button. Pressing a button stopped the timing.

2.2 Results

If a subject's error rate was over 15%, we eliminated that person. This removed one subject each in groups 1 and 2 and 5 in group 3, leaving 17 subjects in each of the three groups. The averages for all groups for the primed words, counting correct responses only, areis in Table 7.

Table 7: Results of lexical decision task

|Identical primes |Blends for Primes |Unrelated primes |

|879 ms |942 ms |949 msa |

The order of reaction time was as predicted, with identical primes the fastest and unrelated primes the slowest, with blends as primes in between. But an analysis of variance showed that the differences did not reach significance at the .05 level. Analyzing various subgroups and correlating reaction times with other factors such as stem completions or familiarity did not result in our finding any significant differences either.

In retrospect, we could also have run the experiment in the opposite direction. That is, rather than looking for traces of automatically activated words, we should have tried to pre-activate the candidate words ourselves and see if that had any effect on the blend identification success. The logic is that if a preconscious lexical identification phase is involved, facilitating this phase should enhance the performance of the whole task. This would be shown if masked priming with a word would facilitate blend identification speed and accuracy.

3. Problems and possibilities

Since our experiments were done many years ago, lexical blends have become even more common that they were then, so subjects might should be even better at processing them now.

However, several variables that we did not consider are important to control for. The first change would be to have a much better way of classifying blends in order to determine how easy or difficult they might be. Frequency, lexical neighbors, context, missing material, and semantic coherence, the factors that Lehrer (1996, 2008) found important, are still relevant, but so are other things we neglected. For one thing, some of the splinters have become bound morphemes, disconnected from their source. Examples are -(a)holic, -thon, -scape, -nomics, -tini, and -licious (Lehrer, 2007). These splinters are often entered in dictionaries as suffixes. Bauer (1983), Adams (1973), Warren (1990), Stein (1977), and others argue that they are combining forms, not suffixes. But classification aside, these items seem to function as bound morphemes without regard to their etymology as splinters. And some of them are in the process of becoming standard clippings.

Secondly, we should have paid more attention to the phonological properties of blends. Insights by Kubozono (1990), Kelly (1998), Plag (2003), Gries (2004) and López-Rua (2004) relevant information on the phonemic and orthographic aspects of blendsare relevant. In addition, the relationship between the phonology and orthography of the stimuli should be examined as well. One important problem is where to divide the blend, especially in cases with two splinters where more than one division is possible as with snizzle < snow + drizzle or swacket < sweater + jacket.

Using the lexical decision task can be a useful tool, but the prime need not be masked. Lexical blends can serve as primes for target words. Blends could also be used as targets in lexical decision tasks. Another interesting test would measure the time it takes subjects to respond to blends. Our prediction is that it will take significantly longer to respond to novel blends than to conventional words and that there will be considerable variation in yes vs. no decisions. For some people a string of letters is not a word until it appears in an authoritative dictionary, while other individuals may use looser criteria. However, instructions on what to count as a word could be an interesting variable.

Masked priming could also be modified by varying the duration of the masked prime. We selected 100 milliseconds, which is longer than the normal duration of 50 or 60 milliseconds. During the discussion of our paper at the Lyon conference, Suszanne Borgwaldt suggested that the priming effect may have been stronger our results may have been better with shorter masked primes because the longer duration in our experiments may have interfered with the automatic implicit responses. Some of the published work (Rastle et al 2000, Forster et al, 1984) may support this conclusion,, although results are mixed because the duration of masked primes interacts with other variables.

There are possibilities for future work on stems, too. Our two lists of stems described above were not matched in any way, and that was a lost opportunity. The stem INF, however, could be completed by a different word from each list. List 1 contained the blend infomercial < information + commercial, while List 2 contained affluenza < affluence + influenza. Table 8 presents the results. Five of the subjects who saw List 1 responded with information, but none of those who saw List 2 did. Of the subjects presented with affluenza, one finished the stem with influenza, and no one from the other group did. Of course, the two words beginning with INF are not comparable, since information is a more common word than influenza, and has info is a standard clipping.

Table 8 Results of stem completion task

| | |Response | |

| | |information |influenza |

|Saw List 1 |infomercial |5 |0 |

|Saw List 2 |afffluenza |0 |1 |

3. Summary and conclusions

The experiments reported here show our attempt to find evidence for automatic processing of lexical blends by measuring the time subjects took to respond, first of all directly by giving them blends with enough time for them to find the targets (sources words) and indirectly with masked primes in a lexical decision task. Since that work was done, blends have become more common, and presumably English speakers have become better at decomposing blends and identifying the target words. We think that lexical decision experiments provide a promising method, but future work will require a better categorization of blends types than we used in order to control for the many variables that need to be identified. We hope that our work will motivate other to continue with this approach.

Endnotes

* We wish to thank Susanne Borgwaldt for her excellent comments and suggestions.

1. Because of equipment problems, we have oral responses for only 20 subjects seeing List 1 and 15 seeing List 2.

2. Susanne Borgwaldt suggested that a good control group would be a group of students who did no participate in the experiment, but complete the stem. The their percentages were similar to 8% and 5% respectively, it could just be that the stem completions were relatively plausible words that would pop up in everyone's mental lexicon, regardless of the previous exposure to blends containing these stems. Similar information might be obtained by examining frequencies and neighbors as well (AL).

References

Adams, Valerie

1973. An Introduction to Modern English Word-Formation. London: Longmans.

Bauer, Laurie

1985. English Word Formation. Cambridge, CUP.

Forster, Kenneth. I.

1985. Lexical acquisition and the modular lexicon. Language and Cognitive Processes 1.2: 87-124

Forster, K. I., C. Davis, C. Schoknechkt, and R. Carter.

1984. Repetition priming and frequency attenuation in lexical access. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10: 680- 698.

Graf, Peter and George Mandler

1984. Activation makes words more accessible, but not necessarily more retrievable. Journal of Verbal Learning and Verbal Behavior, 23.5 .

Graf, Peter and Daniel L. Schacter

1985. Implicit and explicit memory for new associations in normal and amnesic subjects. Journal of Experimental Psychology: Learning, Memory, and Cognition 11.3: 501-518.

Gries, Stefan Th.

2004. Shouldn't it be breakfrunch? A quantitative analysis of blend structure in English. Linguistics 43.2: 639-667.

Kelly, Michael, H.

1998. 'To brunch' or 'to brench': Some aspects of blend structure. Linguistics 36.3:579-590.

Kubozono, Haruo

1990. Phonological constraints on blending in English as a case for phonology- morphology interface. Yearbook of Morphology 3. G. Booij and J. van Marle (eds) 1-20.

Lehrer, Adrienne

1996. Identifying and interpreting blends. Cognitive Linguistics 7.4: 259-390.

Lehrer, Adrienne

2007. Blendalicious. In Lexical Creativity, Texts, and Contexts. Judith Munat (ed.) 115-133. Amsterdam/Philadelphia: John Benjamins.

López-Rua, Paula L.

2004. The categorical continuum of English blends, English Studies. 85: 163-171.

Plag, Ingo

2003. Word-Formation in English. Cambridge: Cambridge University Press.

Rastle, Kathleen, Matt H. Davis, Williams D. Marslen-Wilson, and Lorraine K. Tyler

2000. Morphological and semantic effects in visual word recognitions: A time- course study. Language and Cognitive Processes 15(4.5) 507-537.

Schacter, Daniel I.

1987 . Implicit memory: History and current status. Journal of Experimental Psychology: Learning, Memory, and Cognition 13.3 501-513.

Stein, Gabrielle,

1977. English combining forms, Linguistics 9: 140-148.

Warren, Beatrice

1990. The importance of combining forms, In Contemporary Morphology, W. U. Dressler, H.C. Luschützky, O. E. Pfeiffer, and J. R. Rennison (eds.) 111-132. Berlin, de Gruyter.

................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download