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Jessica Johnston

California State University, Chico

Semantics

December, 2013

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Section 1: Introduction

In chapter nine of her book Words in the Mind, Jean Aitchison surmises that “perhaps

we should imagine [words] as linked together in a gigantic multi-dimensional cobweb, in which

every item is attached to scores of others” (p. 99). Throughout the years, there have been many

theories put forth to explain exactly how words are stored in the mind. One theory that does a

good job explaining the connections between words is the idea of semantic networks or webs.

In this chapter, Aitchison noted that “words seem to be organized in semantic fields, and that,

within these fields, various types of relations exist” (p. 112). Furthermore, each person’s

unique experiences create within him/her unique word connections. Therefore, although some

words may be more often associated, each person will have his or her unique word

connections. Moreover, it is possible that each person has his/her own unique way of storing

and making connections between words. This study looks to see what these connections are

like in specific individuals by looking at word associations they have and how these associations

change over time.

Section 2: ExperimentSection 2.1: Subjects

For this study, I surveyed four people. Two of the people I surveyed four times to see

how their answers changed or stayed the same; these two subjects were the main focus of this

survey. The names of the subjects have been changed for their privacy.

Main Subjects

Melissa: My first subject is my mom. She is in her fifties and is a nurse. She’s a very

caring, motivated, and intellectual person. She is also a problem solver and analytical person.

Robert: My second subject, Robert, is my father. He is a carefree, artistic type person.

He’s very much of a daydreamer and romanticist. He is also a nurse, but is tired and burnt out

from his job.

Secondary Subjects

Alex: My third subject is a 29-year-old male who has a three-year-old son. He didn’t go

to college and is big into weed culture. He was high when he answered this survey.

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Jonathan: My final subject is a 23-year-old college student studying English. He works

with English Learners and want to teach abroad when he graduates.

Section 2.2: Materials

This particular study didn’t require any extra material for the collection of data. The

survey was conducted verbally and transcribed directly into Microsoft Word by the researcher.

Cmaptools was used to create the graphics of the results.

Section 2.3: Procedure

For this study, three very common words were chosen: a noun, adjective, and a verb.

The words chosen were cat, happy, and eat. To retrieve the data, each subject was interviewed

independently from the others. I explained that I was going to say a word and that I wanted

him/her to tell me the first word that came to mind. I then explained that I would repeat the

word he/she had told me and that I wanted him/her to do the same thing over again for a total

of ten words. I wrote down their answers in a table on Microsoft Word. I surveyed two of the

subjects a total of four times over a period of time in order to note any changes in their

answers. I wanted to see if there was a difference between the same subjects yet on different

days. Once the data was collected, I analyzed the connections between words that each person

had.

Section 2.3: Results

Results yielded interesting insight into people’s unique word webs and the types of

connections we have. It was interesting to notice that each person seemed to have their own

unique patterns of associations and ways of connecting words. There seemed to be several

ways in which some of the associations were made: antonyms, collocations, and personal

examples. Moreover, the subjects utilized these types of associations to different degrees,

suggesting that, although our words are stored in a sort of web like fashion, the connections are

based on different things for different people. Furthermore, people’s specific associations

changed throughout time. Below are the tables and charts with the results from each of the

subjects. Following is a discussion of these results.

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Melissa

Survey Number 1 / November 9, 2013Number↓ Words→ Cat↓ Happy↓ Eat↓

1 Meow Sad /Sad Fat2 Catfood Bad / Dad Me3 Stinky (pause) Stalled here/

DiscontentTired

4 Farts Unhappiness Sleep5 Jones Unfulfilling Rest6 Popping Pumpkins Housekeeping River7 Pumpkin Pie Drudgery Happy Memories8 Thanksgiving Day in day out Daddy9 Family Life Life – My life

10 Love Complicated Tiring

Survey number 2 / November 10Number↓ Words→ Cat↓ Happy↓ Eat↓

1 Dog Sad Food2 Bird Mad Fat3 Paradise Bad Beached whale4 Town Dog Sore shoulders5 People Neighbors Chiropractor6 Fun Pot growers

(disturbance)Dr. Erby

7 Party Neighbors Paradise8 Birthday Barking dogs Kalvan9 Cake Ray Happy

10 Fat

November 23 / Survey number 3 Number↓ Words→ Cat↓ Happy↓ Eat↓

1 Dog Sad Food2 Ceasar Sarah Full3 Jessica Negativity Puke4 Ecuador Positivity Work5 Fun Jessica Renal failure6 Parties Ecuador Druggies7 Family Volcano Job security8 Love Banos Good money9 Aturo Fun Good life

10 Sweet Massage Trips to Hawaii

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November 24 / Survey number 4Number↓ Words→ Cat↓ Happy↓ Eat↓

1 Dog Sad Food2 Caesar Sarah Compost bucket3 Stupid Christmas party Gardens4 Circles in the corner

of the fence (caeser’s dirt trails from circling when cars drove by. )

Family Fun

5 Neighbors Fun Rototilling fresh dirt6 Mansfields (the

neighbors)Parties Smells of soil

7 Lamas Christmas Springtime8 Ecuador Spicy smells Beautiful weather9 Equator Fire place Outside golden days

10 Issidore Cozy Air

Robert

November 9 / Survey 1 Number↓ Words→ Cat↓ Happy↓ Eat↓

1 Dog Sad Food2 Fleas Countenance Grows3 Bite Face Farm4 Me Person Country5 I Life Peaceful6 Self Live State7 Help Fast Where8 Need Go Here9 Task Where Now

10 Chore Go Why

November 10 / Survey 2 Number↓ Words→ Cat↓ Happy↓ Eat↓

1 Dog Summer Food2 Animal Time Spoon3 Fur Clock Drawer4 Coat Time Knob5 Warm Herb Glass

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6 Cold Plant Clear7 Shiver Seed Crystal8 Coat Grow Ball9 Clothes Water Play

10 Sad sun Playground

November 23 / Survey 3 Number↓ Words→ Cat↓ Happy↓ Eat↓

1 Dog Face Food2 Hair Smile Natural3 Brush Mouth Countryside4 Teeth Face Pretty5 White Person Subjective6 Color Alive Concept7 Paint Well Thoughts8 Brush Water Mind9 Hair Drink Brain

10 Brown Cup White

November 23 / Survey 4 Number↓ Words→ Cat↓ Happy↓ Eat↓

1 Dog Sad Food2 Tail Countenance Green3 Wag Face Fields4 Nurse Eyes Soil5 Wags Open Tractor6 Retired Box Farmer7 Work Lid Hat8 Play Can Straw9 Hawaii Food Yellow

10 Move Lunch Sunshine

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3.5 Discussion

The data showed above yielded some very interesting results about word webs and the

storage of words in people’s minds. The three main interesting things that were noticed were

that in the span of 10 chain-of-thought responses, the topic or semantic field seemed to

consistently jump every 3 to 4 responses, each subject seemed to have his/her own unique way

of making connections, and answers for the same subjects varied over time meaning that the

connections are not fixed.

It was interesting to note that the subjects seemed to jump semantic field or ideas every

3-5 responses for the most part. This meaning that when given a word such as cat, subjects

would produce words that were more closely connected to cat but then jump to something

much less related on the 3rd, 4th, or 5th word. This new word would take things in a totally

different direction for a few more words and then again jump. Not all of the responses followed

this though. Occasionally, a subject would stay more connected to one idea and did not jump

topics. For the most part, Robert tented to have longer strings of related answers than did

Melissa. However, the few longer strings Melissa had were when she was relating personal

events, and some of Alex’s connections seemed less related than some of the other subjects’

responses.

One of the most interesting discoveries was that each subject seemed to have a very

unique way of making connections between words. For example, Melissa brought in a lot of

personal examples. There were multiple instances where she related things to her own life and

experiences. Robert on the other hand really didn’t do this. He relied far more heavily on

collocation and other ties between words. Jonathan seemed to related things to very specific

examples that had recently happened to him. For example, “eat” was connected to “builder

bar” because he said he had just eaten one.

The third thing which was interesting was that, for the two subjects who I interviewed

multiple times, the responses were not consistent. Although the first response was in many

cases the same, after that, each survey branched off in different directions. It seems that

connections are strengthened and added constantly. What is going on in the mind of a person

at a particular moment determines which connections are stronger at that moment.

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Specific Examples

Following you will find specific examples of these three points illustrated in graphs and

charts along with discussions and explanations. The following charts compare the multiple

surveys done with Melissa and Robert and also the extra data gained from Alex and Jonathan.

These charts are highlighted so that you can see an overview of the points discussed above.

The highlighting refers to the following:

Antonyms

Collocations

Personal Examples

As was previously discussed, each person has his/her own unique way of making connections. You will see that each subject relies more heavily on one of these than the others do. Furthermore, you can see the difference in survey answers over time for Melissa and Robert. Following the charts are word webs which discuss specific instances which are noteworthy. The connections made by the subjects are denoted by the black arrowed lines. Red lines are possible connections that could exist but were not stated by the subject. The boxes are color coded by semantic field or topic.

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Melissa November 9 November 10 November 23 November 23

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Word >> Cat Cat Cat Cat1 Meow Dog Dog Dog2 Catfood Bird Ceasar Ceasar3 Stinky Paradise Jessica Stupid4 Farts Town Ecuador Circles in the

corner of the fence

5 Jones People Fun Neighbors6 Popping

PumpkinsFun Parties Mansifields

7 Pumpkin Pie Party Family Lamas8 Thanksgiving Birthday Love Ecuador9 Family Cake Aturo Equator10 Love Fat Sweet Issidor------------------------ ------------------------ --------------------- ---------------------- -----------------------Word >>> Happy Happy Happy Happy1 Sad Sad Sad Sad2 Dad Mad Sarah Sarah3 Discontent Bad Negativity Christmas party4 Unhappiness Dog Positivity Family5 Unfulfilling Neighbors Jessica Fun6 Housekeeping Pot growers

(disturbance)Ecuador Parties

7 Drudgery Neighbors Volcano Christmas8 Day in day out Barking dogs Banos Spicy smells9 Life Ray Fun Fire place10 Complicated Massage Cozy------------------------ ------------------------ ---------------------- ----------------------

-----------------------

Word >>> Eat Eat Eat Eat1 Fat Food Food Food2 Me Fat Full Compost bucket3 Tired Beached whale Puke Gardens4 Sleep Sore shoulders Work Fun5 Rest Chiropractor Renal failure Rototilling fresh

dirt6 River Dr. Erby Druggies Smells of soil7 Happy Memories Paradise Job security Springtime8 Daddy Kalvan Good money Beautiful

weather9 Life – My life Happy Good life Outside golden

days10 Tiring Trips to Hawaii Air

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Robert November 9 November 10 November 23 November 23Word >> Cat Cat Cat cat1 Dog Dog Dog Dog2 Fleas Animal Hair Tail3 Bite Fur Brush Wag4 Me Coat Teeth Nurse5 I Warm White Wags6 Self Cold Color Retired7 Help Shiver Paint Work8 Need Coat Brush Play9 Task Clothes Hair Hawaii10 Chore Sad Brown Move

Word >>> Happy Happy Happy Happy1 Sad Summer Face Sad2 Countenance Time Smile Countenance3 Face Clock Mouth Face4 Person Time Face Eyes5 Life Herb Person Open6 Live Plant Alive Box7 Fast Seed Well Lid8 Go Grow Water Can9 Where Water Drink Food10 Go Sun Cup Lunch

Word >>> Eat Eat Eat Eat1 Food Food Food Food2 Grows Spoon Natural Green3 Farm Drawer Countryside Fields4 Country Knob Pretty Soil5 Peaceful Glass Subjective Tractor6 State Clear Concept Farmer7 Where Crystal Thoughts Hat8 Here Ball Mind Straw9 Now Play Brain Yellow10 Why Playground White Sunshine

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Alex

Sound Connection: this is something that only showed up in Alex’s response.

Number↓ Words→ Cat↓ Happy↓ Eat↓1 Dog Sad Drink2 Pound Happy Satisfaction3 Cruella de Vil Sad Happy4 Corolla Happy Sad5 Toyota Flowers Scared6 Japanese Sun Sleepy7 Typhoon Kite Rest8 Radiation Wind Happy9 Chrynobal Jacket Yellow

10 Russian Warm Flowers

Jonathan

Number↓ Words→ Cat↓ Happy↓ Eat↓1 I can has

cheeseburgerSmily face emoticon Builder bar (he was

eating it on the way here)

2 Lolcat Blackboard collaborate (he uses it at work)

Protein

3 Meme TLP (where he works) Meat4 Richard dawkins Blackboard learn Safeway5 Atheism Online Education Produce (he said, now

I’m thinking of the last

6 Christianity Sarah Tretchter Trechter7 Jesus Safeway (he saw her

at safeway)Grammar

8 Church Produce Grammar textbook (image of our textbook)

9 Church bells Banana ( he ate a banana today)

Notepad

10 Bell tower at CSU Monkey Pen

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Melissa’s word web for “Cat” Survey 1

This web shows clearly the jump from topic to topic every 3-4 words. Furthermore, it

highlights Melissa’s tendency to use personal examples. Cat food made Melissa think of the

word stinky which lead to the word farts. This word then threw her into a personal example and

story. Farts went to Jones which is referring to Melissa’s older sister and family. The connection

between fart and Jones is that they are extremely religiously conservative and considered the

word fart almost as a bad word and therefore would call it “popping pumpkins,” which is

something we always thought was a bit funny and silly. The word pumpkin in popping pumpkins

made her thinking of pumpkin pie which then took her into thoughts of thanksgiving and family.

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Melissa’s web for Happy survey 3

This word web further shows Melissa’s tendency to connect things to personal

experiences. The word happy made her think of the antonym sad, which then made her think of

the name Sarah. Sarah was a friend of mine who was constantly morose and depressed with life

no matter what. She was the epitome of “negativity” which is why she then thought of that

word. She then again goes for the antonym “positivity.” This word made her think of me,

someone who she thinks of as being very happy and positive. The rest of the words all related

to each other because my name threw her into words that relate to a time when she visited

Ecuador while I was living there. We went to a town called Banos which is located in the

mountains under a volcano. While there, we had fun and also got massages.

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Jonathan’s map for

Another subject who relied heavily on personal examples was Jonathan. Unlike Melissa,

his examples seemed to relate far more heavily on immediate examples or recent events. For

example, online education made him think of Sarah Tretchter one of his teachers. This then

made him think of Safeway because he had seen her there. He then thought of produce and

then specifically a banana because he said he had eaten one that day. In the survey of the word

eat, he thought of a specific example of something he had recently ate as well. It seems that

recent events were more on the forefront of his mind and affected which words he thought of.

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Robert’s word web for “cat” Survey 1 and 2

Unlike Melissa or Jonathan, Robert didn’t seem to rely on personal examples much at

all. Instead, many of his connections were based on collocations. In this particular survey, bite is

a verb that is often used with a pronoun and therefore he thought of the pronoun me after bite.

Again, self and help are often collocated together and therefore from self he went to help. In

the second survey, he goes with the collocation of fur coat. Furthermore, the second survey

also shows some other interesting things. First, he uses partial antonyms with the words

warm/cold. But more interestingly, the word coat showed up twice in this one survey.

However, it made the subject think of two different things because of the situation it was

embedded in. It showed up first when thinking of animals and therefore brought up the word

warm. However, when it comes later, in a different context, it made him think of clothes.

Therefore, a particular word association seems determined by what other words have been

recently activated in a person’s mind.

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Robert’s word web for “cat” 2

Robert’s word for Happy – survey # 4

One interesting example was Robert’s survey for the word happy. Most all of the other

surveys jumped categories every few words, however, this one appears to be quite

homogenous. The topic of gardening is something that Robert is very much into, and therefore,

perhaps he has stronger connections in this area which helped to keep him on topic.

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Alex’s word web for eat

Unlike Robert’s previous homogenous example, Alex provides us with one that

seemingly jumps less obvious connections and associations. The connections between sad and

scared and between scared and sleepy seem particular unique. They are not connections I

would draw.

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Mellissa Cat surveys comparison

It is interesting to note that although there are certainly changes over time, there are

still some interesting comparisons. These surveys took place over a span of two weeks. They

were conducted on the 9th, 10th, and 24th of November. The two on the 24th were conducted

within about 10 minutes of each other. As you can see, the two from the 24th share a lot of

similarities even though they are a little different. The topic of Ecuador comes up both times

although through a completely different means. In the 4th survey, Melissa has neighbors (the

Mansfields) who have Alpacas, though she thought of them as Lamas during the survey. The

idea of lamas connected her to Ecuador because there are many lamas and Alpaca things for

sale there. The connection to Ecuador in the 3rd survey came from Jessica because she had lived

in Ecuador. Furthermore, surveys done two weeks apart also shared some similarities. Surveys

2 and 3 both shared the connection of fun and parties, and survey 1 and 3 shared connections

of family and love. Perhaps then, instead of saying that peoples connections are constantly

changing, what changes is the mind that accesses the connections. If certain other things are

activated in a mind, then perhaps other words are chosen over others.

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Conclusion Word connections seem to be very unique and slippery things. There is no doubt that

we all have ways of connecting words in our minds, and a web like model is a logical

assumption that is backed up by the way that words seemed to be associated to one another.

However, these associations are not necessarily fixed, or if they are indeed fixed, then the mind

that jumps around on them is not necessarily fixed. Although it is impossible to know for sure

exactly how words are stored and subsequently retrieved, this data does show that each person

seems to have his/her own unique way of making connections. Some people relate things more

to personal example while others utilize other connections such as collocations, antonyms, etc.

Furthermore, the associations people have vary throughout time. Even after ten minutes the

associations are changed. Ten minutes doesn’t seem time enough for a brain to change word

storage location. Therefore, I suggest that perhaps in our mind word webs are somewhat static

but what changes is the mind that jumps around on those words. The mind chooses certain

words over others depending upon what particular ideas and thoughts are lit up in someone’s

mind at a particular time. Therefore, although pathways may light up more than others

depending upon the thought process, the pathways themselves do not actually change, of

course, this is just a guess as there is no real way of knowing for sure.