Concrete & Abstract Words
Difference between concrete and abstract words.
It was enunciated in the beginning of this discussion Opens in new window that words Opens in new window are not directly related to the things and experiences they describe.
Language Opens in new window is basically an abstract system of signs. However, there are levels of abstraction.
For example, calling a cow a “cow” is less abstract and conveys a more precise meaning than calling it “an animal” or “livestock”. So does identifying someone as “Daniel” rather than referring to him as “friend” or “man”.
Classification of Words
Words can be loosely classified as concrete and abstract . A dictionary will tell you that concrete words are signs which name a thing, or a class of things, as opposed to naming a quality or attribute.
In contrast to concrete words, abstract words are the names for qualities and attributes. Such words as “love”, “humanity”, “justice”, “pleasure”, “clever”, and “worship” do not denote an actual object.
You can see from these examples that concrete words carry more specific meanings than abstract words.
Since the referents for concrete words can be perceived by the senses—they are able to be seen, heard, and even felt—there is a smaller margin of meaning error than in the case of abstract words. Hence, there is likely to be less misunderstanding between communicator and recipient.
Generally, abstract words have feelings, emotions, attitudes and ideas as their referents. Since the referent is a concept rather than a thing, words such as “democracy”, “ethics”, “honest”, “crowd”, or “freedom” are likely to be different for different people. There is thus more likely to be a breakdown in communication (cf. Andersch, Staats & Bostrom 1969).
To finalize this discussion, we summarize the main problems that have been identified in connection with denotation and connotation Opens in new window , and concrete and abstract words:
- The connotative meaning of a word may overshadow and distort its historical (denotative) meaning.
- The referent of a word may be different for different people.
- The referents of abstract words are highly individualized because they do not exist in actuality (cf. Andersch, Staats & Bostrom 1969:123).
This study is a series. See next page!
- Language Opens in new window
- Word & Meaning Relatedness Opens in new window
- Denotative vs Connotative Meaning of Words Opens in new window
- Difference Between Concrete and Abstract Words Opens in new window
- Sapir Whorf Hypothesis Opens in new window
Adapted from: S. Steinberg's Introduction to Communication Course Book 1: The Basics
Pasco-Hernando State College
- Concrete and Abstract Words; Denotation and Connotation; Figurative Comparison
- The Writing Process
- Paragraphs and Essays
- Unity and Coherence in Essays
- Proving the Thesis/Critical Thinking
- Standard English, Using a Dictionary, Using a Thesaurus
- Bias and Discriminatory Language; Cliches; Repetitiveness; Wordiness
- Active and Passive Voice; Point of View/Person
Concrete and Abstract Words
A concrete word is a word that refers to a specific, tangible item. Concrete words clearly identify and define. Abstract words are general and not specific.
Our society should primarily be concerned with raising children properly. The word society is not concrete since it is not tangible.
Parents should be primarily concerned with raising children properly. The word parents is concrete since it is tangible.
The need for clear reference is one of the problems with using second person you in writing. The reference is too general and not concrete.
Unclear : You should know what your children are doing.
This sentence is poorly constructed. I, as the reader, would be confused if I have no children. This sentence isn’t meant to refer to me. Here is more clear phrasing.
Corrected : Parents with children living at home should know what their children are doing.
Unclear: The air is bad today.
This sentence is very general. What air? What’s bad about it? Here are sentences that more specifically explain:
Corrected : The pollen level in the air is high today.
The air is thick with smoke from the nearby forest fire.
The traffic from the highway down the block causes a foul smell in the air.
Denotation and Connotation
Denotation is the dictionary meaning of a word. Connotation is what meanings are attached to the word.
House is a place where people live. Home is a place where people live. However, the meanings attached to home are very different.
Some words have positive or negative connotations. For example, would you rather be childlike or childish ? Childlike has a positive connotation while childish has a negative connotation.
Denotation : Small in proportion to height or length
Positive connotation : Slim, Trim, Svelte
Negative connotation : Skinny, Boney, Scrawny
Literal comparisons use concrete and specific analysis based on the dictionary definitions. Figurative comparisons use references to different experiences to evoke images. Here are three sets of examples, each set using a literal and figurative comparison.
Rose petals look like thin, curved shavings of wood which are dyed red. This is a literal comparison.
Rose petals are as soft as a feather and as sweet as a perfume. This is a figurative comparison.
She was shy.
She was like a shrinking violet.
The road was cracked and full of debris.
The road looked as though a bomb has exploded on it.
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Concrete Nouns vs. Abstract Nouns
Concrete nouns and abstract nouns are broad categories of nouns based on physical existence: Concrete nouns are physical things that can be seen, touched, heard, etc.; abstract nouns are nonphysical ideas that cannot be perceived through the senses. For example, you can touch a muscle , which makes it a concrete noun, but you cannot touch strength , which makes it an abstract noun.
All nouns are either concrete or abstract, but never both at the same time. It can sometimes be hard to know which is which, so this guide explains their differences and how to tell them apart, with lists of both concrete noun examples and abstract noun examples.
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What are concrete nouns?
Concrete nouns describe physical things that can be sensed: seen, touched, heard, smelled, or tasted. Most nouns are concrete nouns—for example, rocks , butterflies , grandmothers , and the Great Sphinx of Giza . Even invisible things, including air (which can be felt) and music (which can be heard), are concrete nouns.
Microscopic things, such as bacteria and atoms , are also concrete nouns because they exist in the physical world. Even imaginary or fantasy things, such as unicorns and the character Katniss Everdeen , are concrete nouns—but only if they represent something that can be sensed, even if only in fictional writing .
Specifically, concrete nouns consist of these:
- Living things: nouns that relate to people, animals, plants, and other organisms, both general ( humans , trees ) and specific ( Billie Eilish , California redwood )
- Places : nouns that relate to locations, both general ( city , mountain ) and specific ( Lagos , Mount Fuji )
- Material things: nouns that represent things we can perceive through the senses—not only physical objects, such as furniture and statues , but also things like dances and noise
Examples of concrete nouns
- prime minister
- Danny DeVito
- Santa Claus
- social media
- The Bluest Eye (novel)
What are abstract nouns?
By contrast, abstract nouns are nonphysical things that cannot be sensed. These are ideas, emotions, and other intangible things that exist in our minds instead of in the physical world. For example, intelligence and education are abstract nouns because they’re immaterial concepts (you can’t touch education), but place names such as schools and universities are concrete nouns because they can be perceived through our senses.
Abstract nouns have many different categories, but some of the most common include these:
- Emotions/feelings: nouns that describe a mental state or mood, such as anger and comfort
- Characteristics: nouns that describe a personality trait, feature, quality, virtue, or vice, such as bravery and elegance
- Philosophical concepts: nouns that describe complex ideas of logic, principle, or ideals, such as morality and socialism
- States of being: nouns that describe a condition or way of existence, such as chaos and luxury
- Time: nouns that relate to time—both common, such as minute and year , and proper, such as Wednesday and July
Differentiating between abstract nouns and concrete nouns isn’t always easy, but there is a quick trick that can help. If a word uses a suffix to turn itself into a noun, it’s an abstract noun. For example, the adjective cute takes the suffix – ness to make the abstract noun cuteness . Some common suffixes used by abstract nouns include these:
- -acy/-cy — normalcy , privacy , vacancy
- -ance/-ence — maintenance , persistence , importance
- -ism — feminism , atheism , patriotism
- -ity — velocity , animosity , creativity
- -ment — agreement , entertainment , government
- -ness — business , cleanliness , happiness
- -ship — friendship , internship , relationship
- -sion/-tion — compassion , consideration , demolition
Abstract noun examples
Emotions/feelings, characteristics, philosophical concepts.
States of being
Concrete nouns vs. abstract nouns
Concrete nouns and abstract nouns are two important classifications for nouns to help understand the natures of the things they represent. However, when it comes to grammar and usage, the difference is rather meaningless.
Concrete nouns and abstract nouns follow the same grammar rules as all general nouns. Both can turn into possessive nouns with the same construction; for example, you can talk about beauty’s price just as you can talk about a book’s price . Likewise, both can form compound nouns , such as the concrete noun trash can and the abstract noun entertainment business .
Concrete and abstract noun FAQs
Concrete nouns describe physical things that can be sensed: seen, touched, heard, smelled , or tasted. They include all living things, places, and material things—even invisible things, such as bacteria and music .
Abstract nouns describe conceptual things that cannot be sensed. They include all emotions, feelings, characteristics, philosophical concepts, states of being, and time. For example, independence , beauty , love , anger , and Monday are all abstract nouns.
How to tell the difference between concrete nouns and abstract nouns?
To tell if a noun is concrete or abstract, ask yourself whether it can be sensed—i.e., can it be seen, heard, touched, smelled, or tasted? If it can be sensed, then it’s a concrete noun; if not, then it’s abstract. Another way is to look for suffixes like – ness and -ment : Nouns that end in these suffixes are usually abstract, such as happiness and entertainment .
The Magic of Knowing When to Use Concrete vs. Abstract Language
A few years ago, I was on the way to the airport when I got the text every traveler dreads: my flight had been canceled. I’d been on the road for a couple days, and was looking forward to getting home, so this was less than ideal.
To make matters worse, the airline had tried to rebook me, but rather than a direct flight later that day, I’d been rebooked on a connecting flight the next one. Now I was really pissed, so I called customer service to try to fix things.
The agent on the other end of the line was less than helpful. Rather than actually listening, or trying to really understand the problems, they kept walking through what felt like a script. Using stock phrase after stock phrase in an attempt to show they “cared” rather than putting in the work of actually caring.
The kind Uber driver who’d been forced to listen to the conversation offered his condolences, and we ended up striking up a conversation. I mentioned how frustrated I was but also how bad I felt for the customer service representatives who had to deal with everyone’s problems. It wasn’t their fault that the flight had been canceled, yet there they were, fending off angry people like me all day long, one after the other.
It seemed to me like a tough job, but the Uber driver said it was quite the contrary. He mentioned that his daughter worked in customer service for one of the airlines and loved it. In fact, she was so good at making customers happy that the airline had promoted her to teach other agents how to be more effective.
At first, I was surprised. Making customers happy in this context seemed quite difficult. Most callers are dealing with canceled flights, delays, or lost bags, and it wasn’t like the agent could snap their fingers and magically make the problems go away.
But as I thought about it more, I started to wonder: If his daughter was so good at dealing with difficult situations, what was she saying that helped patch things up? Beyond what agents could offer (e.g., a credit or alternate flight), might there be certain ways of communicating that make customers more satisfied?
Beyond what agents could offer (e.g., a credit or alternate flight), might there be certain ways of communicating that make customers more satisfied?
To study that question, Grant Packard and I assembled a data set of hundreds of customer service calls to a big online retailer: someone from Arkansas whose luggage wouldn’t unlock; someone from St. Louis whose shoes were defective; and someone from Sacramento who needed help returning a shirt that didn’t fit.
With the help of a transcription company and a team of research assistants, we turned the recordings into data. We transcribed the calls, separated out what the agent and customer had said, and even measured vocal features such as pitch and tone.
Each customer called for a different reason, but many calls followed a familiar script. The agent introduced themselves, the customer outlined whatever issue they were having, and the agent tried to solve it. Attempting to sort out why the luggage wouldn’t unlock, figuring out what was wrong with the shoes, or helping the customer return the shirt. The agent would look in their system, or chat with a manager, and collect whatever information was needed. Then, after hopefully resolving the issue, they’d explain what they’d found or done, see if the customer had any more questions, and say goodbye.
But while the calls themselves had a similar structure, the outcomes were quite different. Some customers were happy with the service and found the agent quite helpful. Others, not so much. Not surprisingly, part of this was driven by what customers were calling about. Some called about problems with their accounts, and others called about trouble with an order. Some called about bigger issues and others called about smaller ones.
But even controlling for what people called about, customer demographics, and dozens of other factors, how agents talked played an important role. A certain way of speaking boosted customer satisfaction.
And to understand that way of speaking, we have to understand what’s known as linguistic concreteness.
Three ways to apply it are to: (1) make people feel heard, (2) make the abstract concrete, and (3) know when it’s better to be abstract.
A service representative answering a request to find a pair of shoes, for example, could say that they would go look for them, those shoes , or those lime green Nikes. Someone responding to an inquiry about a delivery could say the package will be arriving there , at your place , or at your door . And someone discussing a refund could say, we’ll send you something , a refund, or your money.
In all three examples, the latter versions use more concrete language. Those lime green Nikes is more concrete than them , at your door is more concrete than there , and your money back is more concrete than refund , which is more concrete than something . The words used are more specific, tangible, and real.
These variations might seem like simple turns of phrase, but they had an important impact on how customers felt about the interaction.
Using concrete language significantly increased customer satisfaction. When customer service agents used more concrete language, customers were more satisfied with the interaction and thought the agent had been more helpful.
When customer service agents used more concrete language, customers were more satisfied with the interaction and thought the agent had been more helpful.
And the benefits of linguistic concreteness extended beyond how customers felt. When we analyzed almost a thousand email interactions from a different retailer, we found similar effects on purchase behavior. When employees used more concrete language, customers spent 30 percent more with the retailer in the following weeks.
And it turns out there are other benefits to linguistic concreteness, too.
Using concrete language to present ideas, for example, makes them easier to understand . Similarly, analysis of thousands of tech support pages found that pages that used more concrete language were rated as more helpful. Compared to using more abstract language (e.g., “About the security partial trust allow list”) using more concrete language (e.g., “How to split and move the keyboard” or “Check your battery and charge your watch”) made it easier for readers to understand what the content was about and find it more helpful in resolving their questions.
Concrete language also makes things more memorable. Readers are more likely to remember concrete phrases (e.g., “rusty engine”) and sentences (e.g., “when an airplane blasts down the runway and passengers lurch backward in their seats”) than abstract ones (e.g., “available knowledge” or “moving air will push up against a surface placed at an angle to the airflow”).
Not surprisingly, then, using concrete language has a host of beneficial consequences. It holds people’s attention, encourages support, and drives desired action.
In fact, linguistic concreteness even affects parole board decisions. When prisoners apologize for their actions, those who give more concrete explanations for their transgressions are more likely to be granted parole.
Given all the benefits of concrete language, one question is: Why we don’t use it more often? After all, if concrete language makes things easier to understand, remember, and feel positively toward, why would anyone ever speak or write abstractly?
While concrete language is great for increasing understanding, or for making complex topics easier to comprehend, when it comes to things like describing a company’s growth potential, abstract language is better, because while concrete language focuses on the tangible here and now, abstract language gets into the bigger picture.
Want to help people understand a complex idea, feel heard, or remember what was said? Using concrete language is going to be more effective.
Take Uber, the company best known for its ride-hailing app. When Uber was founded in 2009, it would have been easy to describe the business as exactly that: “A smartphone app that makes it easier to get a taxi, connecting passengers and drivers and reducing wait time.” This description is perfectly accurate and provides a good sense of what the company does. It’s also highly concrete. It uses specific language to help people understand the nature of Uber’s business.
But that’s not the only way Uber could be described. In fact, one of the cofounders actually positioned the company quite differently. He described it as “a transportation solution that is convenient, reliable, and readily accessible to everyone.”
In some ways, the difference might seem minor. Both descriptions give some sense of the general space Uber is in and what it’s trying to do. But while the first description is quite concrete, the way the cofounder actually pitched the business is much more abstract. Rather than focusing on ride hailing per se, which is much narrower in scope, calling Uber a “transportation solution” taps the broader problem Uber is trying to solve.
That, in turn, increased investment because it made the potential market seem much larger. A ride-hailing app? I can think of a few people who might need that or a few situations in which it might be useful.
But a transportation solution? Wow, that seems a lot broader. Lots of people and companies could use something like that, and it seems to have lots of applications.
We’re not just a fintech startup, we’re a solutions provider. We’re not just a device builder, we’re a life improver.
Rather than focusing on one niche, abstract language makes the market seem widespread. And given that larger growth potential, a company seems like a much more promising investment.
Consequently, whether it’s better to use concrete or abstract language depends on the outcome we’re trying to achieve.
If we want people to think our idea has potential, or that we’re a forward-thinking visionary, abstract language is more effective.
Want to help people understand a complex idea, feel heard, or remember what was said? Using concrete language is going to be more effective. Using verbs that focus on actions (e.g., walk, talk, help, or improve), for example, rather than adjectives (e.g., honest, aggressive, or helpful). Talking about physical objects or using evocative language to help them see what we’re saying.
But if we want people to think our idea has potential, or that we’re a forward-thinking visionary, abstract language is more effective.
More generally, when trying to make language either more concrete or more abstract, one helpful approach is to focus on either the how or the why .
Want to be more concrete? Focus on the how . How does a product meet consumer needs? How does a proposed new initiative address an important problem? Thinking about how something is or will be done encourages concreteness. It focuses on the feasibility and helps generate concrete descriptions.
Want to be more abstract? Focus on the why . Why does a product meet consumer needs? Why does a proposed new initiative address an important problem? Thinking about why something is good or right encourages abstractness. It focuses on its desirability and helps generate abstract descriptions.
Excerpted from Magic Words: What to Say to Get Your Way by Jonah Berger. Published by Harper Business. Copyright © 2023 by Jonah Berger. All rights reserved.
Jonah Berger is a marketing professor at the Wharton School at the University of Pennsylvania and the author of Contagious , Invisible Influence , The Catalyst , and, most recently, Magic Words.
Further Reading & Resources
- Berger, J. (2023). Magic Words: What to Say to Get Your Way. New York, NY: Harper Business. ( Link )
- Warren, N. L., Farmer, M., Gu, T., & Warren, C. (2021). Marketing Ideas: How to Write Research Articles that Readers Understand and Cite. Journal of Marketing 85 (5), 42–57. ( Link )
- Begg, I. (1974). Recall of meaningful phrases. Journal of Verbal Learning and Verbal Behavior 11 (4), 431-439. ( Link )
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Table of Contents
When you hear the term “abstract,” what comes to mind? A painting by Jackson Pollock? And if you hear the word “concrete,” what’s the first thing you think of? A foundation? Or a sidewalk? Your brain pulled these answers quickly. Why? Because you are most familiar with these words in those settings. However, as a writer, you must be equally familiar with these terms regarding language and business communication. So, in the tug-of-war of abstract language vs. concrete language, which will emerge the clear winner?
Abstract vs. Concrete Language
Let’s breakdown the differences between abstract language and concrete language.
- Includes general language and intangible qualities, ideas, or concepts.
- It is often vague and open to interpretation.
- A reader may find it hard to pin down the exact meaning.
- Includes specific word usage.
- It is especially helpful in business communication.
- It is clear, compelling, and easily understood.
A skilled writer knows how to properly use and mix all levels of language, including abstract and concrete. When you can deftly implement and weave language on multiple levels, your writing becomes more interesting . And you can reach audiences on a deeper level.
Examples of Abstract Language
We use abstract terms every day. Life would get pretty boring without ideas and concepts floating around, challenging our minds to try to define them. However, when we need to give instructions, specific advice, or motivate our audience, we need to add some concrete to the mix. Failing to do so can result in misunderstandings.
Here are a few examples of how abstract language can be vague :
- Our company is looking for a flexible team player. ( Flexible? For what? The office gymnastics tournament? )
- I am an experienced office manager. ( Why should I believe you? You offered no examples of your experience. )
- ZYX Marketing will integrate actionable solutions. ( Classic B2B marketing fluff—big words, no substance. )
Examples of Concrete Language
Concrete language is specific . It gets right to the point and removes any ambiguity. And it provides the extra details that connect your reader to your message.
Here are a few examples of concrete language:
- We build custom software that allows HR department heads to design employee manuals.
- The interviewer guidelines offer real-life examples and sample questions you can modify and use.
- The accounting department has asked all employees to submit reports using Excel spreadsheets.
Concrete language can also leave a mental impression because it connects to our senses. Like this:
- The red Toyota Corolla jerked back and forth as it went down the bumpy road. ( Did you “see” the color red? Or “feel” the car jerking over the bumps? )
- The lawyer listened intently as the young woman relayed the details of the accident, wiping her tears as she softly spoke. ( Could you “see” her distress? Did you picture the lawyer leaning in closer, trying to “hear” her words? )
A person is more likely to remember details of a sentence or paragraph when concrete language and terms are used. Give your reader something they can relate to, picture, or feel.
Which is Better? And Why?
Concrete language is preferred in business communication. It gives your readers knowledge about you, your company, and how you differ from your competitors. Also, it can motivate and convince people to buy your product or pay for a service. Concrete wording is powerful.
Check out the following sentences. Which one do you like better? Which one is clear and memorable?
Example 1: Our company can help you meet all your goals.
Example 2: At JLS Marketing, we offer website design, email campaigns, and posting to social media to help you turn leads into customers.
The first sentence is too abstract—it doesn’t provide any value. However, the second sentence defines who you are, what you will do, and how it will help your client. It is attention-grabbing and full of details.
Remember, the more abstract your writing is, the less likely you are to make your point. This can spell disaster in business. So, aim for concrete language—specific language that is easily understood and vivid. And avoid hiding behind broad generalizations.
Classifying Abstract and Concrete Words
Words are like kittens—they don’t stay in one place for long, they jump onto things they shouldn’t, and can be a bit naughty at times. A word may not always fall into the “abstract” or “concrete” category. At times, words can overlap in the level of abstraction and meaning. So, you may need to add context or modifiers to tweak a sentence. Look for ways to provide additional information that will give the reader a better understanding. For example:
Abstract: The supervisor felt it was a complex situation.
Concrete: The HR supervisor recognized the complexity of the employee’s allegations of sexual harassment from a co-worker.
So, to be an effective business writer, you need to understand the differences in abstract vs. concrete language. And using concrete language in business writing is the gold standard in presenting information.
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Mini review article, concrete vs. abstract semantics: from mental representations to functional brain mapping.
- 1 Laboratory of Behavioral Neurodynamics, St. Petersburg State University, Saint Petersburg, Russia
- 2 Department of Clinical Medicine, Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Aarhus, Denmark
The nature of abstract and concrete semantics and differences between them have remained a debated issue in psycholinguistic and cognitive studies for decades. Most of the available behavioral and neuroimaging studies reveal distinctions between these two types of semantics, typically associated with a so-called “concreteness effect.” Many attempts have been made to explain these differences using various approaches, from purely theoretical linguistic and cognitive frameworks to neuroimaging experiments. In this brief overview, we will try to provide a snapshot of these diverse views and relationships between them and highlight the crucial issues preventing this problem from being solved. We will argue that one potentially beneficial way forward is to identify the neural mechanisms underpinning acquisition of the different types of semantics (e.g., by using neurostimulation techniques to establish causal relationships), which may help explain the distinctions found between the processing of concrete and abstract semantics.
Defining Concreteness and Abstractness
One can often encounter in the literature such terms as “concrete and abstract concepts,” “concrete and abstract words,” or “concrete and abstract semantics.” What is the difference? In psycholinguistic and cognitive frameworks, concepts may be termed as the knowledge about a particular category ( Barsalou et al., 2003 ), as a combination of atomic units of information and meaningful relationships between those units ( Payne et al., 2007 ), or as “a mental representation of a class or individual which deals with what is being represented and how that information is typically used during the categorization” ( Smith, 1989 , p. 502). Such mental (internal or cognitive) representations ( Paivio, 1990 ) are widely investigated in cognitive psychology, psycholinguistics, philosophy of mind and related fields ( Carruthers and Cummins, 1990 ), but often without a clear connection to neural representations, which are more commonly addressed in brain research, neuroscience and neuroimaging. It is believed that the most important concepts (called lexical concepts) have an expression in the language in the form of individual words (= are labeled by words; Margolis and Laurence, 1999 ) and are thereby “our representation of word meaning” ( Murphy, 2002 , p. 392). In this regard, in most concept studies, linguistic stimuli are used and thus the terms “concept,” “word semantics,” and “word meaning” are often used interchangeably. Traditionally, words/concepts are subdivided into concrete and abstract types, and this distinction is considered in many contemporary psycholinguistic and cognitive studies. As often claimed, concrete concepts/words have clear references to material objects (e.g., dog, house ), whereas references of abstract ones are not physical entities, but more complex mental states (e.g., thought, happiness ), conditions ( uncertainty ), situations ( encounter ), and relationships ( employment ) ( Borghi and Binkofski, 2014 ). However, even this seemingly simple distinction is not unequivocal. For instance, Myachykov and Fischer (2019) have argued that, in addition to this phenomenological dimension of abstractness, there are also sensorimotor and contextual aspects, and the same word/concept may be both concrete or abstract depending on different dimensions. Sensorimotor and contextual dimensions are, in turn, determined by individual life experience of lexicon acquisition and usage. Therefore, one way to extricate from this tangle could be studying processing of novel words, whose meanings are not yet represented in the participants’ minds. Such an approach may solve the problem of conceptual confusion – the first obstacle to establishing of clear links between theoretical descriptions and the brain mechanisms which underlie representations of these different knowledge types in the brain.
Research of concrete and abstract concepts has a long history; a landmark event in its modern period was Paivio’s seminal article “Abstractness, imagery, and meaningfulness in paired-associate learning” ( Paivio, 1965 ). Numerous behavioral experiments using lexical decision, recognition, word naming, and other behavioral tasks demonstrated that concrete concepts, in comparison with abstract ones, are better remembered ( Schwanenflugel et al., 1992 ), recognized ( Fliessbach et al., 2006 ), faster read and comprehended ( Schwanenflugel and Shoben, 1983 ), and faster learnt ( Mestres-Missé et al., 2014 ). Similar results were revealed with respect to the processing of concrete and abstract verbs ( Alyahya et al., 2018 ) and definitions ( Borghi and Zarcone, 2016 ). This advantage of concrete over abstract semantics is usually called “concreteness effect”; to help explain it, Paivio suggested the so-called dual-coding theory (DCT, Paivio, 1990 ) which posits two functional systems associated with semantic memory: verbal-based and imagery-based (non-verbal). These representational systems are interrelated and can be active independently or in parallel. According to DCT, whereas the verbal system may be responsible for coding both concrete and abstract concepts linguistically, the non-verbal imagery system is primarily involved in coding concrete – but not abstract – concepts, enhancing their processing and leading to behaviorally observed advantages ( Kuiper and Paivio, 1977 ).
Notably, some investigations showed that concrete words elicit faster responses in lexical decision task only when there is no context information helping to understand the meaning; when context is available, the concreteness effect is reduced or absent ( Schwanenflugel and Shoben, 1983 ). These observations were explained by the context-availability theory (CAT), which claims that concrete and abstract concepts have different amount of semantic associations: concrete concepts have stronger associative connections with fewer contexts, while abstract concepts have weaker associative connections with a larger number of contexts. This, in turn, means that providing relevant context information may eliminate the “concreteness effect” leading to equally efficient processing of both semantic types.
A similar view on the distinctions between concrete and abstract words suggests that they are represented in mind in qualitatively different ways ( Crutch, 2006 ). This hypothesis was based on the study of different types of semantic errors in patients with deep dyslexia. According to this account, concrete words have hierarchical semantic structure, which relies on categorical interrelationship (superordinate and co-ordinate), whereas abstract representations have, on the contrary, associative architecture (with connections between words commonly used together).
Other cognitive frameworks, rather than stressing the differences between abstract and concrete processing mechanisms, focus on searching for their similarities. For instance, the embodied cognition view on language grounds semantic representations in bodily functions (perception, action) and proposes that abstract word processing, in the same way as that of concrete words, relies, at least in part, on sensorimotor systems ( Glenberg et al., 2008 ; Pulvermüller, 2013 , see Borghi et al., 2017 , for review of embodied views on concrete/abstract concepts). Indeed, a comparison of acquisition and processing of abstract semantics in children with typical language development, atypical development, and autism showed no significant differences between these groups, also indicating the absence of specific mechanisms of abstract knowledge acquisition ( Vigliocco et al., 2018 ). This, however, still does not exclude a more substantial contribution of the linguistic system into the abstract processing found in some studies (e.g., Sakreida et al., 2013 ).
In cognitive linguistics, a somewhat similar approach is offered by the so-called conceptual metaphor theory (CMT), an influential theoretical framework, according to which abstract concepts may be understood in reference to more concrete words by using metaphors ( Lakoff and Johnson, 1980 ). However, in development, metaphors become available later than basic abstract knowledge as such; furthermore, it has been argued that not every abstract concept can be fully understood metaphorically, i.e., in terms of concrete words ( Borghi and Zarcone, 2016 ).
One theoretically contentious issue in accounting for concrete and abstract features of word semantics is that of a relationship between “concreteness” and “emotionality”. Many authors consider words connected to emotions (for example, love , joy, fear ) as a kind of abstract concepts (see, e.g., Dreyer and Pulvermüller, 2018 ) because they lack specific subject-relatedness. However, consideration of abstractness from embodied, rather than purely phenomenological dimension allows referring to emotions as concrete (embodied in individual experience) items ( Myachykov and Fischer, 2019 ). Furthermore, some authors divide all concepts into three types: concrete, abstract and emotional ( Altarriba and Bauer, 2004 ). This latter approach seems somewhat controversial, as it does not appear to be based on uniform classification criteria. Moreover, both concrete and abstract words may possess less or more emotional meaning (consider, e.g., joy vs. justice , or cake vs. pencil ); further, this may depend on a person’s individual experience. To put it differently, it is uncertain why, in the Altarriba and Bauer (2004) classification, such words as win or jeopardy were included into the group of abstract words while daughter and dentist were treated as concrete words, even though their meaning clearly carries emotional aspects.
Perhaps a more convincing approach links emotional experience with abstract concepts ( Kousta et al., 2011 ). The so-called affective grounding hypothesis (AGH) makes several specific suggestions in this respect ( Lenci et al., 2018 ). First, abstract and concrete concepts differ in the extent of involvement of two types of information: experiential (sensory, motor, and affective) and linguistic (verbal associations); this clearly resonates with Paivio’s dual-coding account. Second, concrete concepts are mainly grounded in sensory-motor information, whereas abstract word meanings are underpinned predominantly by linguistic and emotional information. Finally, the prevalence of these specific types of information plays a crucial role in acquisition as well as further representation of both concrete and abstract concepts ( Vigliocco et al., 2009 ). As a side note, this approach provides a way to define specific semantics as a flexible combination of experiential and linguistic features, suggesting that abstractness and concreteness are relative terms, and not a simple binary distinction.
This view is complemented by a suggestion about a significant role of social experience in acquisition and representation of abstract concepts ( Barsalou and Wiemer-Hastings, 2005 ), since linguistic experience is acquired directly or indirectly in social interactions which makes it particularly crucial in building up abstract knowledge. Borghi et al. (2018) support this idea, considering words as social tools (WAT theory) and suggesting that abstract representations are more likely to involve linguistic and social experience than concrete ones (because of the absence of material references with objects), especially during their acquisition ( Borghi and Binkofski, 2014 ; Borghi and Zarcone, 2016 ). WAT is an attempt to create an integral theory of abstract concepts from the point of embodied and grounded approach to cognition. We concur with Borghi et al. (2018) ’ on the importance of exploring the differences between concrete and abstract concept acquisition but emphasize the need to focus on the dynamics of this acquisition process, not just on its outcomes.
A different avenue for disentangling various accounts and interpretations of cognitive phenomena is offered in neuroscience, which focuses on identifying their underlying brain mechanisms, by investigating neuroanatomical substrates and neurophysiological dynamics of cognitive processes in the brain. In simple terms, if comprehension of concrete and abstract concepts is underpinned by different brain mechanisms, this can be investigated by scrutinizing neural activation patterns using functional brain mapping (e.g., EEG, MEG, fMRI or PET), or, to address causality, using neurostimulation techniques (TMS, tDCS) and/or brain-damaged patients. Neuropsychological data indicate that concrete words are more resistant to different brain injuries than abstract ones ( Binder et al., 2005 ), suggesting at least partially different neural systems supporting these knowledge types. This suggestion is corroborated by a number of neuroscientific studies showing overlapping but not identical brain areas involved in abstract vs. concrete stimulus processing (see Montefinese, 2019 , for a concise review).
However, there are still multiple contradictions across available neuroimaging studies ( Wang et al., 2010 ), which has so far prevented neuroscience from resolving the dispute between theoretical accounts. Greater activation in such areas as middle and superior temporal gyrus (STG, MTG) and left inferior frontal gyrus (IFG) was associated with the processing of abstract concepts ( Binder et al., 2005 ; Sabsevitz et al., 2005 ; Fliessbach et al., 2006 ; Pexman et al., 2007 ). Concrete concepts, in turn, have been shown to activate ventral anterior part of the fusiform gyrus ( Sabsevitz et al., 2005 ; Bedny and Thompson-Schill, 2006 ; Fliessbach et al., 2006 ), which was also confirmed in an fMRI study of concrete word acquisition ( Mestres-Misse et al., 2007 ). Other areas exhibit a less clear picture. For example, enhanced activation for abstract, as opposed to concrete, concepts has been observed in the anterior temporal region (ATL) in a number of studies ( Tettamanti et al., 2008 ; Binder et al., 2009 ; Wang et al., 2010 ), whereas other experiments revealed the opposite, activation in ventral ATL specific for concrete concepts ( Peelen and Caramazza, 2012 ; Visser et al., 2012 ; Robson et al., 2014 ), or an equal involvement of ventrolateral ATL for both concept types ( Hoffman et al., 2015 ). It appears that while some such studies do not always have a clear basis in theoretical cognitive accounts, others mainly set out to prove the dual-coding theory. For instance, the results of EEG studies by Holcomb et al. (1999) speak in favor of the context-extended version of dual-coding account, which integrates DCT and CAT, at the neurophysiological level. Their experiments showed significant differences between brain responses to concrete and abstract words for the N400 component, a negative ERP wave associated with lexico-semantic processing: word concreteness leads to a greater negativity of the N400, especially in anterior areas, decreasing over posterior sites ( Holcomb et al., 1999 ). Similar concreteness effect – stronger N400 – was also found in a study of acquisition of novel concrete and abstract semantics ( Palmer et al., 2013 ). Concrete words also elicit larger N700 responses comparing with abstract ones even if they are matched for their context-availability and imageability ( Barber et al., 2013 ), which, as the authors asserted, could not be explained by context-extended DCT. In turn, Pexman et al. (2007) unambiguously concluded that their neurophysiological data favors Barsalou’s theory of semantic representation over dual-coding and context-availability theories, while Borghi et al. (2018) find neurophysiological support for the WAT theory, further deepening the theoretical divide.
There are virtually no studies of concrete vs. abstract semantics using brain stimulation techniques (which could provide the much-needed causal evidence), with only a handful of TMS papers that suggested prefrontal and motor areas to take part in abstract word comprehension (e.g., Vukovic et al., 2017 ). One way to apply brain stimulation is to investigate changes in the activity of the motor cortex and corticospinal activation during comprehension ( Hoffman et al., 2010 ). For example, the processing of abstract and concrete phrases differentially modulates cortico-spinal excitability ( Scorolli et al., 2012 ). However, any association with movement will cause activation of the mirror neurons in the motor system ( Rizzolatti and Sinigaglia, 2016 ), and given the great variability in motor cortex responses to TMS ( Fedele et al., 2016 ), it is very difficult to disentangle the specific and non-specific effects of different semantic types and brain stimulation.
Clinical data distinguishing between abstract and concrete concepts are extremely rare. While there are some cases (“case studies”) of specific impairments in abstract or concrete concept comprehension, separately, they are based on very limited observations ranging from one to four patients at most ( Warrington and Crutch, 2005 ; Crutch, 2006 ; Tree and Kay, 2006 ). Furthermore, such conceptual comprehension impairments are confounded by a variety of other co-morbidities (e.g., dyslexia in Crutch, 2006 ), while the definitions of abstractness and concreteness used by the authors vary and do not always conform to the status quo in the field. In essence, the available clinical data are so far unable to provide a clear picture of distinctions between these semantic types.
Whereas cognitive accounts of semantic representations, abstract semantics in particular, have gone a long way in recent decades, their neural counterparts so far suffer from the lack of studies and contradictions in the available data. The reasons for these contradictions could be many and include different properties of stimulus materials used, stimulation parameters, imaging modalities, and experimental tasks. One key difficulty lies with balancing basic psycholinguistic and physical properties of abstract and concrete words under investigations in a particular study; the lack of such balance confounds any differential results. A related issue that appears important is that most studies deal with pre-existing representations that are confounded by their surface properties, previous learning trajectories, daily use, and existing associations, all of which may obscure the results. In addition, the concrete-abstract dichotomy may not be complete and more fine-grain distinctions have been suggested: for example, action-related and object-/visually related concrete words, mental state-, emotion-, and mathematics-related abstract words ( Dreyer and Pulvermüller, 2018 ). Further, rather than a dichotomy, there may be a multidimensional concreteness-abstractness continuum, along which words may vary, sometimes falling into both categories depending on the specific context ( Myachykov and Fischer, 2019 ).
One way to circumvent these difficulties could be to assess the process of acquisition of novel concrete and abstract semantics in laboratory settings, using stimuli with fully controlled and systematically modulated semantic, physical and psycholinguistic parameters. By observing the learning process behaviorally and its counterparts in the brain, it may be possible to elucidate the systems that take part in building up novel representations and the degree to which they differ between semantic types. To avoid confounds related to different modes of acquisition of abstract and concrete semantics, the learning regime should be maximally matched between semantic conditions, using, for instance, context-based inference or direct instruction ( Atir-Sharon et al., 2015 ). To assess the learning outcomes, an elaborate testing of lexical, semantic, and contextual levels of acquisition is desirable; ideally, the assessment should be done both immediately and after a consolidation period (e.g., after an overnight sleep, Davis et al., 2009 ).
Whereas many acquisition studies use either exceptionally novel word forms (pseudowords) ( De Groot and Keijzer, 2000 ; Mestres-Missé et al., 2014 ) or unfamiliar words of foreign languages with established semantics ( van Hell and Mahn, 1997 ), it is crucial to disentangle the mechanisms of learning the new word form and its phonology from those of acquiring the semantics per se ( Partanen et al., 2017 ). This, in our view, is best achieved by training well-matched phonologically and phonotactically legal forms both as such (i.e., surface forms only) and in conjunction with novel semantics – rather than attaching familiar semantics to novel native word forms or foreign words ( Leminen et al., 2016 ).
There is still a predominance of studies dedicated to investigation of learning mechanisms of concrete rather than abstract semantics; they are targeted more often owing to their more obvious link with sensorimotor experience ( Mahon and Caramazza, 2008 ) that lends itself readily to experimental manipulation. While it may be straightforward to learn new names for new objects using, e.g., word-picture matching, creating a new abstract category in an experimental setting is much more challenging. One way to address this could be adopting abstract concepts from cultures other than that of experimental participants.
On another note, most available studies use correlational measures, e.g., showing distinct activation patterns accompanying perception. Clearly, causal evidence is also needed to demonstrate functional relevance of such distinctions. Outside of limited patient studies, such evidence is presently lacking. The use of neurostimulation techniques (such as TMS or tDCS) to influence both comprehension and acquisition of concrete and abstract semantics may provide the much-needed evidence for the involvement of particular brain areas in representing specific semantic types. For example, Fiori et al. (2011) revealed that the application of anodal tDCS over Wernicke’s area while learning new words significantly improved the accuracy and decreased latencies in a picture-naming task, while another study ( Flöel et al., 2008 ) showed faster and better associative verbal learning with the anodal tDCS over posterior left perisylvian areas, compared to sham. We are not aware of any similar studies comparing concrete and abstract semantics and their acquisition; this could be the target for future investigations.
To conclude, the literature suggests cognitively and neurophysiologically distinct systems that support abstract and concrete representations in mind and brain. Yet, the data available to date, particularly with respect to abstract semantics, do not allow for clear delineation of the underlying brain systems and thus explaining the effects found behaviorally. To fill these gaps in the field, future studies should use a combination of rigorously matched behavioral regimes, controlled modes of presentation, a comprehensive set of tasks to assess behavioral outcomes at different times, and different neuroimaging tools able to assess both the complex dynamics of word comprehension and the causal relationships between brain structures and representation types. One way to help disentangle the mechanisms underpinning different semantic representations is to focus on their acquisition in controlled experimental settings.
All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.
This study was supported by the RF Government grant contract no. 14.W03.31.0010.
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Keywords : concrete and abstract semantics, concreteness effect, mental representation, brain, memory trace, psycholinguistics, functional brain mapping
Citation: Mkrtychian N, Blagovechtchenski E, Kurmakaeva D, Gnedykh D, Kostromina S and Shtyrov Y (2019) Concrete vs. Abstract Semantics: From Mental Representations to Functional Brain Mapping. Front. Hum. Neurosci. 13:267. doi: 10.3389/fnhum.2019.00267
Received: 27 February 2019; Accepted: 17 July 2019; Published: 02 August 2019.
Copyright © 2019 Mkrtychian, Blagovechtchenski, Kurmakaeva, Gnedykh, Kostromina and Shtyrov. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
This article is part of the Research Topic
Brain-Behaviour Interfaces in Linguistic Communication