<p>There are some interdisciplinary areas in CS that may be similar to what you're looking for. These areas are often considered &quot;applied&quot;, in the sense that they restrict their research to a certain application domain of CS and the relevance of results is mainly measured by the impact of the result on the application domain. However, these areas are also at times &quot;theoretical&quot;, in the sense that an effective way to achieve results is applying the techniques and rigor from TCS and mathematics in general. Of course, this means that most projects will eventually <em>have</em> to produce a software implementation, unlike most areas in TCS.</p>
<p>While it is true that human behaviour cannot (at least, at the present) be fully captured by rigorous models, the increasing rate of digitization means that mathematical models will nevertheless be implicitly applied to human behaviour. Therefore, we can either study the models in order to select models that are the least bad, or hope that the models which are implicitly constructed end up being good.</p>
<p>One group of areas deals with computation involving models that arise from studying or managing human behaviour. Economics, as mentioned, is an example. Matching theory (with problems such as the <a href="https://en.wikipedia.org/wiki/Stable_marriage_problem" rel="nofollow noreferrer">stable marriage problem</a>) in particular has received plenty of attention from economics, CS, and combinatorics. Somewhat related is the area of computational social choice, which deals with questions such as voting and fair division of goods (see e.g. the <a href="https://doi.org/10.1017/CBO9781107446984" rel="nofollow noreferrer">Handbook of Computational Social Choice (2016)</a> )</p>
<p>Another group of areas is human computer interaction. Take visualization, for example. The goal of visualization is to somehow produce images that allow humans to learn from data. As such, the final test is always whether the visualization is of use to the human reading it. Nevertheless, we have enormous and complex data that we cannot visualize by hand, so we again have no choice but to make a model of the features that yield a &quot;good&quot; visualization. Some (often) more theoretical areas related to visualization are <a href="https://en.wikipedia.org/wiki/Graph_drawing" rel="nofollow noreferrer">graph drawing</a>, <a href="https://en.wikipedia.org/wiki/geovisualization" rel="nofollow noreferrer">geovisualization</a>, and computational cartography.</p>
<p>Visualization deals with humans interacting with the output of a computational process. The input (or entire interaction loop) the human provides also at times leads to interesting theoretical questions. The field of digital humanities has some examples, mostly in information retrieval and (possibly interactive) querying.</p>

CC BY-SA 4.0
2021-08-16T16:11:18.373Z
2021-08-19T07:42:57.073Z
2021-08-19T07:42:57.073Z
Discrete lizard
<p>Yes, absolutely!  This is a blossoming new field in the social sciences that a lot of people are excited about right now.  The phrase to look for is <a href="https://en.wikipedia.org/wiki/Computational_social_science" rel="noreferrer">&quot;computational social science&quot;</a>.</p>
<p>There is a a lot of work in graph theory and networks in particular.  Some researchers to look into are:</p>
<ul>
<li><a href="https://en.wikipedia.org/wiki/Mark_Newman" rel="noreferrer">Mark Newman</a></li>
<li><a href="https://en.wikipedia.org/wiki/Aaron_Clauset" rel="noreferrer">Aaron Clauset</a></li>
<li><a href="https://humannaturelab.net" rel="noreferrer">Nicholas Christakis</a></li>
<li>(Also see the work going on at the <a href="https://www.santafe.edu/" rel="noreferrer">Santa Fe Institute</a>)</li>
</ul>
<p>Additionally, there is a lot of work on developing new deep learning methods to analyze sentiments in text analysis, e.g., social media posts.  There is a lot of theory behind these new methods.  For example, a popular one is <a href="https://en.wikipedia.org/wiki/Sentiment_analysis" rel="noreferrer">sentiment analysis</a>.</p>
<p>Another topic to look into is category theory.  If you want to build purely theoretical mathematical models of social phenomena, that's probably going to be the way to do it.  E.g. <a href="https://www.sciencedirect.com/science/article/pii/0010028580900146" rel="noreferrer">a paper where they did just that</a>.</p>
<p>So yes, there are many reasons theoretical computer science is important in the social sciences, and we are just beginning to understand how they can inform each other.  This is an exciting time to be in your position!</p>
<p>EDIT: Fixed the link, thanks Damiano Mazza!</p>

CC BY-SA 4.0
2021-08-17T08:19:47.913Z
I'm not very familiar with category theory. Could you elaborate what the advantage of the language of category theory is for social sciences over the language of graph theory?
Discrete lizard
CC BY-SA 4.0
2021-08-17T08:40:51.597Z
@Discretelizard: The premise of your question is misguided; category theory is not an alternative to graph theory. In this context, its main benefit of it is that it gives a uniform language for expressing constructions from game theory, automata theory, control theory, and spectral graph theory, and furthermore this language is amenable to analysis using linear-algebraic techniques  (i.e., what category theorists call monoidal categories). It's the **same** techniques, but expressed in a way which generalises more easily.
Neel Krishnaswami
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2021-08-17T08:43:48.283Z
@NeelKrishnaswami I see. Perhaps it would have been more correct to ask what category theory can give us in this context that graph theory cannot. Nevertheless, you answered my question.
Discrete lizard
CC BY-SA 4.0
2021-08-17T09:45:01.047Z
I do think that category theory has the potential to offer interesting perspectives for linking social sciences and computer science.  However, judging from the abstract (I do not have access to the full paper, unfortunately) the link given as an example of the application of category theory to social sciences does not seem to contain any category theory at all (also, when I read "recent paper" I expected something more recent than 2007, but that's subjective :-) ).  Maybe there's a mistake in the link?
Damiano Mazza
CC BY-SA 4.0
2022-02-24T05:04:08.480Z
I find it very hard to call the work done by the names you mentioned (Newman, Clauset, Christakis) TCS.
These people are network scientists, by training some physicists, some computer scientists, some economists, etc. and they certainly do work on what's broadly considered "computational social science", but it's not TCS.
Note, although network theory uses some graph theory, it actually relies a lot more on fields like statistical physics, and I'd be very surprised if I ever see a work I'd call TCS by a network theorist (I'm quite familiar with both field).
nara
CC BY-SA 4.0
2022-02-24T05:06:41.760Z
Also, computational social science is usually relatively applied, and A LOT less abstract than TCS.
There is TCS work in social science, but mostly done in economic theory and micro economic theorists work on that. This might be also the only overlap in scholars (but I wouldn't say in research) between network science and TCS, e.g. Matthew Jackson.
nara
CC BY-SA 4.0
2021-08-17T08:10:34.323Z
2021-08-17T10:53:31.650Z
2021-08-17T10:53:31.650Z
Anonymous
<p>It seems to me that your best chance at applying TCS to social sciences is to apply it to study problems in economics. In particular, one can use TCS to argue that certain tasks required in economics are computationally infeasible. For a concrete example of this, see the following write-up:
<a href="https://m-cacm.acm.org/magazines/2011/5/107705-computational-complexity-and-information-asymmetry-in-financial-products/fulltext#R5" rel="noreferrer">https://m-cacm.acm.org/magazines/2011/5/107705-computational-complexity-and-information-asymmetry-in-financial-products/fulltext#R5</a></p>

CC BY-SA 4.0
2021-08-16T07:18:46.210Z
Thanks for the advice, I appreciate it. Know the funny part? I'm actually looking at other fields like sociology/anthropology.
wonderinghuh
CC BY-SA 4.0
2021-08-16T06:54:53.137Z
2021-08-16T06:54:53.137Z
Reijo Jaakkola
<p>I used to study economics, and the answer is yes. In 2019/2020 Nobel Laureate Paul Milgrom gave the marshall lectures in cambridge with the title &quot;Market Design When Resource Allocation is NP-Hard&quot;. I believe that there is plenty of intersection between game theory and TCS, (e.g., search algorithmic game theory books on amazon).</p>
<p><a href="https://www.econ.cam.ac.uk/Marshall_Lecture" rel="nofollow noreferrer">https://www.econ.cam.ac.uk/Marshall_Lecture</a></p>

CC BY-SA 4.0
2021-08-17T14:13:55.920Z
2021-08-17T14:13:55.920Z
riemann_lebesgue
<p>&quot;Stupid&quot; is subjective and judgmental, but there are certainly meaningless, trivial, or uninteresting questions. Or at least sometimes they can <em>seem</em> meaningless until someone comes along and imbues them with meaning. Let's take math, for example. The search for the smallest positive real might have been meaningless before nonstandard analysis was discovered. Similarly, the search for an integer that's both even and odd might seem silly at first, but perhaps might actually make sense in some paraconsistent logic.</p>
<p>&quot;Trivial&quot; means easily solvable by anyone with a minimal set of commonly available tools, not a research question. &quot;Uninteresting&quot; means lacking a compelling motivation or structure. Number theory is famous for being able to generate endless problems not solvable by current techniques, and number theorists are rather picky about which ones they choose to devote time to. Their criteria, I imagine, include: which are the likeliest to be amenable to the tools we do have? Which hold the promise of shining light on new structure or leading to new tools and techniques?</p>
<p>Finally, I'll attempt an answer to the OP. A &quot;stupid&quot; question is one that the research community agrees, by broad consensus, is not a research question -- and is posed, as a research question, by someone who is in a position to know better.</p>

CC BY-SA 4.0
2021-08-16T08:34:09.433Z
2021-08-16T08:34:09.433Z
Aryeh
<p>I won't say it is impossible, but to me it seems... challenging at best.  Social science deals with the behavior of humans, and humans are complex.  TCS deals with mathematics and computer algorithms, which can be precisely and rigorously modelled.  Those two don't seem well-matched to me.  My suspicion is that it will be difficult to apply techniques from TCS to human motivation and behavior.  I'm not saying there is no hope for your vision, but I'm suggesting you inform yourself about the challenges and have a thoughtful plan for how you plan to address them.</p>

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2021-08-18T02:07:14.537Z
Thank you for your insightful comment. Couldn't TCS be used to formalize some axioms that are noted from certain social phenomena and then jump off into forming mathematical theory from said axioms? In fact, couldn't you use use the process of reverse mathematics to determine axioms  (from a quantitatively weak qualitative framework in social science/humanities) and then work from there?
wonderinghuh
CC BY-SA 4.0
2021-08-18T17:08:44.457Z
Social phenomena do not admit axioms - they are inherently too subjective and vague to describe that way. Consider Richard Feynman's remark: *“We can’t define anything precisely. If we attempt to, we get into that paralysis of thought that comes to philosophers… one saying to the other: you don’t know what you are talking about! The second one says: what do you mean by ‘talking’? What do you mean by ‘you’? What do you mean by ‘know’?”*
Zev Chonoles
CC BY-SA 4.0
2021-08-21T20:31:45.933Z
You can still model people with axioms and make good predictions. Seems like this line of questioning will ultimately lead you to the field of economics, however, rather than TCS
Karagounis Z
CC BY-SA 4.0
2022-02-24T05:15:07.677Z
This is simply not true. There is a relatively considerable chunk of microeconomic theory that is quite close to TCS. Harvard has an EconCS group. Also places like Stanford, Northwestern, UPenn, Cornell, etc. have people working in this area. In fact Game Theory is a field that's developed both by economists and computer scientists (perhaps disproportionally by economists), and I would consider most of the theoretical work in game theory TCS, wouldn't you? You can find people from both sides that cross into the other, e.g. Annie Liang at Northwestern Econ, or Vincent Conitzer at Duke CS.
nara
CC BY-SA 4.0
2021-08-16T06:05:59.393Z
2021-08-16T06:05:59.393Z
D.W.
<p>I'm very new to this field - technically not <em>in</em> it but want to be. I'm very early in my academic career (sophomore at a community college) but decided that I want to add a math major along with my computer science major in order to really dive into the field (when I transfer to a 4 year that is).</p>
<p>However - I used to be a social science major a lot time ago (before I left school and decided to come back), and some of the concepts have stuck with me from my old major. I decided to throw myself in the TCS field now and in the future, but I also believe that TCS could provide insight into some of the problems I encountered in social science.</p>
<p>The problems themselves aren't important to mention here, but the aspect of trying to turn social science phenomenona into isomorphic TCS problems (which could then possibly have some mathematical framework that then could formalize and clear up <strong>some</strong> of the qualitative vagueness I ran into as a social science major!) is heavily appealing - not to mention it would really challenge me as a TCS/mathematician intellectually, which I do appreciate.</p>
<p>Now you've read the above and have some insight, does that seem naive or stupid? I have worries I will be laughed out of TCS conferences (&quot;look at this guy trying to turn gender into a computation problem!&quot;) for even trying this. Will I be taken seriously (I do have to mention that I will, under no circumstances, say such foolishness as &quot;gender is Turing complete&quot;) or will I be seen as a 'waste of a PhD' ( I do plan on getting one of those in TCS).</p>
<p>TCS in its own right is awesome, full stop. I can easily imagine myself doing purely TCS for the rest of my life. But is trying to apply it to non-STEM (social science and even Humanities academic problems ) a fools errand?</p>
<p>Thank you for your time reading this.</p>

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2021-08-16T13:30:38.967Z
It sounds like mathematical modeling/scientific computing might be a better fit for your vision than theoretical CS? CS Theory is focused on proving things about extremely precise, well-defined problems. Taking fuzzy concepts from other fields and imposing enough structure on them to make them amenable to computation is a very noble and worthwhile endeavor, but it doesn't sound to me like Theory.
user168715
CC BY-SA 4.0
2021-08-16T14:28:45.020Z
@user168715 I feel  that this is the best answer. If you just happen to have some links  at hand to useful resources for the OP to learn about what mathematical modeling and scientific computing are and how/where to learn more about those fields, I'd suggest you add those and make it into an actual answer.
Vincent
CC BY-SA 4.0
2021-08-16T15:07:35.253Z
I'd recommend you look into the field of [multi-agent systems](https://en.wikipedia.org/wiki/Multi-agent_system), which I like to think of as the intersection of computer science and behavioral economics. The [stable matching problem](https://en.wikipedia.org/wiki/Stable_marriage_problem) is an example of a problem in this area. A lot of the work in this field is about designing algorithms that find incentive-compatible solutions to problems like these.
Finn
CC BY-SA 4.0
2021-08-17T09:42:41.267Z
Just noting that the OP has changed considerably (original title was "Is there a 'stupid' question or 'stupid' research field in theoretical computer science?"). This renders my answer somewhat moot.
Aryeh
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2021-08-17T10:31:54.833Z
@Aryeh You are supposed to answer the *question*, not its title. The question didn’t change at all.
Emil Jeřábek
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2021-08-18T02:01:38.180Z
@user168715 Thanks for your reply. Not to get philosophical, but what is *theory* to you?
wonderinghuh
CC BY-SA 4.0
2021-08-18T02:19:10.750Z
@wonderinghuh I guess the easiest answer is the descriptive one: the area of research problems studied by the community that publishes at conferences like FOCS and STOC.
user168715
CC BY-SA 4.0
2021-08-18T07:32:26.493Z
@wonderinghuh I suppose it should be mentioned that "TCS" is probably considered rather narrow. Within the CS community, researchers in "TCS" are often said to be roughly those who want to publish at FOCS and STOC. (this is narrower than the scope of this site, IIRC) But to an average CS undergraduate, the research done by people who'd rather publish at SODA or ESA (or e.g. SOCG, PODC, POPL, etc.) would also be "theoretical" compared to what they get taught in class. So, don't focus too much on the label "TCS", but instead look at what sort of research different communities are doing.
Discrete lizard
<soft-question><application-of-theory><social-sciences>
Can theoretical computer science be applied in social sciences?
wonderinghuh
# Can theoretical computer science be applied in social sciences?

(Asked by: username_0 on 2021-08-16)

I'm very new to this field - technically not *in* it but want to be. I'm very early in my academic career (sophomore at a community college) but decided that I want to add a math major along with my computer science major in order to really dive into the field (when I transfer to a 4 year that is).

However - I used to be a social science major a lot time ago (before I left school and decided to come back), and some of the concepts have stuck with me from my old major. I decided to throw myself in the TCS field now and in the future, but I also believe that TCS could provide insight into some of the problems I encountered in social science.

The problems themselves aren't important to mention here, but the aspect of trying to turn social science phenomenona into isomorphic TCS problems (which could then possibly have some mathematical framework that then could formalize and clear up **some** of the qualitative vagueness I ran into as a social science major!) is heavily appealing - not to mention it would really challenge me as a TCS/mathematician intellectually, which I do appreciate.

Now you've read the above and have some insight, does that seem naive or stupid? I have worries I will be laughed out of TCS conferences ("look at this guy trying to turn gender into a computation problem!") for even trying this. Will I be taken seriously (I do have to mention that I will, under no circumstances, say such foolishness as "gender is Turing complete") or will I be seen as a 'waste of a PhD' ( I do plan on getting one of those in TCS).

TCS in its own right is awesome, full stop. I can easily imagine myself doing purely TCS for the rest of my life. But is trying to apply it to non-STEM (social science and even Humanities academic problems ) a fools errand?

Thank you for your time reading this.

**Tags:** soft-question, application-of-theory, social-sciences
> **Comments:**
> **username_1**: It sounds like mathematical modeling/scientific computing might be a better fit for your vision than theoretical CS? CS Theory is focused on proving things about extremely precise, well-defined problems. Taking fuzzy concepts from other fields and imposing enough structure on them to make them amenable to computation is a very noble and worthwhile endeavor, but it doesn't sound to me like Theory.  
> **username_2**: @user168715 I feel  that this is the best answer. If you just happen to have some links  at hand to useful resources for the OP to learn about what mathematical modeling and scientific computing are and how/where to learn more about those fields, I'd suggest you add those and make it into an actual answer.  
> **username_3**: I'd recommend you look into the field of [multi-agent systems](https://en.wikipedia.org/wiki/Multi-agent_system), which I like to think of as the intersection of computer science and behavioral economics. The [stable matching problem](https://en.wikipedia.org/wiki/Stable_marriage_problem) is an example of a problem in this area. A lot of the work in this field is about designing algorithms that find incentive-compatible solutions to problems like these.  
> **username_4**: Just noting that the OP has changed considerably (original title was "Is there a 'stupid' question or 'stupid' research field in theoretical computer science?"). This renders my answer somewhat moot.  
> **username_5**: @Aryeh You are supposed to answer the *question*, not its title. The question didn’t change at all.  
> **username_0**: @user168715 Thanks for your reply. Not to get philosophical, but what is *theory* to you?  
> **username_1**: @wonderinghuh I guess the easiest answer is the descriptive one: the area of research problems studied by the community that publishes at conferences like FOCS and STOC.  
> **username_6**: @wonderinghuh I suppose it should be mentioned that "TCS" is probably considered rather narrow. Within the CS community, researchers in "TCS" are often said to be roughly those who want to publish at FOCS and STOC. (this is narrower than the scope of this site, IIRC) But to an average CS undergraduate, the research done by people who'd rather publish at SODA or ESA (or e.g. SOCG, PODC, POPL, etc.) would also be "theoretical" compared to what they get taught in class. So, don't focus too much on the label "TCS", but instead look at what sort of research different communities are doing.  

---

## 6 answers

### Answer by username_13 on 2021-08-16. Score: 16 | Accepted answer

I won't say it is impossible, but to me it seems... challenging at best. Social science deals with the behavior of humans, and humans are complex. TCS deals with mathematics and computer algorithms, which can be precisely and rigorously modelled. Those two don't seem well-matched to me. My suspicion is that it will be difficult to apply techniques from TCS to human motivation and behavior. I'm not saying there is no hope for your vision, but I'm suggesting you inform yourself about the challenges and have a thoughtful plan for how you plan to address them.

> **Comments:**
> **username_0**: Thank you for your insightful comment. Couldn't TCS be used to formalize some axioms that are noted from certain social phenomena and then jump off into forming mathematical theory from said axioms? In fact, couldn't you use use the process of reverse mathematics to determine axioms  (from a quantitatively weak qualitative framework in social science/humanities) and then work from there?  
> **username_14**: Social phenomena do not admit axioms - they are inherently too subjective and vague to describe that way. Consider Richard Feynman's remark: *“We can’t define anything precisely. If we attempt to, we get into that paralysis of thought that comes to philosophers… one saying to the other: you don’t know what you are talking about! The second one says: what do you mean by ‘talking’? What do you mean by ‘you’? What do you mean by ‘know’?”*  
> **username_15**: You can still model people with axioms and make good predictions. Seems like this line of questioning will ultimately lead you to the field of economics, however, rather than TCS  
> **username_10**: This is simply not true. There is a relatively considerable chunk of microeconomic theory that is quite close to TCS. Harvard has an EconCS group. Also places like Stanford, Northwestern, UPenn, Cornell, etc. have people working in this area. In fact Game Theory is a field that's developed both by economists and computer scientists (perhaps disproportionally by economists), and I would consider most of the theoretical work in game theory TCS, wouldn't you? You can find people from both sides that cross into the other, e.g. Annie Liang at Northwestern Econ, or Vincent Conitzer at Duke CS.  

---

### Answer by username_6 on 2021-08-16. Score: 12

There are some interdisciplinary areas in CS that may be similar to what you're looking for. These areas are often considered "applied", in the sense that they restrict their research to a certain application domain of CS and the relevance of results is mainly measured by the impact of the result on the application domain. However, these areas are also at times "theoretical", in the sense that an effective way to achieve results is applying the techniques and rigor from TCS and mathematics in general. Of course, this means that most projects will eventually *have* to produce a software implementation, unlike most areas in TCS.

While it is true that human behaviour cannot (at least, at the present) be fully captured by rigorous models, the increasing rate of digitization means that mathematical models will nevertheless be implicitly applied to human behaviour. Therefore, we can either study the models in order to select models that are the least bad, or hope that the models which are implicitly constructed end up being good.

One group of areas deals with computation involving models that arise from studying or managing human behaviour. Economics, as mentioned, is an example. Matching theory (with problems such as the [stable marriage problem](https://en.wikipedia.org/wiki/Stable_marriage_problem)) in particular has received plenty of attention from economics, CS, and combinatorics. Somewhat related is the area of computational social choice, which deals with questions such as voting and fair division of goods (see e.g. the [Handbook of Computational Social Choice (2016)](https://doi.org/10.1017/CBO9781107446984) )

Another group of areas is human computer interaction. Take visualization, for example. The goal of visualization is to somehow produce images that allow humans to learn from data. As such, the final test is always whether the visualization is of use to the human reading it. Nevertheless, we have enormous and complex data that we cannot visualize by hand, so we again have no choice but to make a model of the features that yield a "good" visualization. Some (often) more theoretical areas related to visualization are [graph drawing](https://en.wikipedia.org/wiki/Graph_drawing), [geovisualization](https://en.wikipedia.org/wiki/geovisualization), and computational cartography.

Visualization deals with humans interacting with the output of a computational process. The input (or entire interaction loop) the human provides also at times leads to interesting theoretical questions. The field of digital humanities has some examples, mostly in information retrieval and (possibly interactive) querying.


---

### Answer by username_7 on 2021-08-17. Score: 11

Yes, absolutely! This is a blossoming new field in the social sciences that a lot of people are excited about right now. The phrase to look for is ["computational social science"](https://en.wikipedia.org/wiki/Computational_social_science).

There is a a lot of work in graph theory and networks in particular. Some researchers to look into are:

* [Mark Newman](https://en.wikipedia.org/wiki/Mark_Newman)
* [Aaron Clauset](https://en.wikipedia.org/wiki/Aaron_Clauset)
* [Nicholas Christakis](https://humannaturelab.net)
* (Also see the work going on at the [Santa Fe Institute](https://www.santafe.edu/))

Additionally, there is a lot of work on developing new deep learning methods to analyze sentiments in text analysis, e.g., social media posts. There is a lot of theory behind these new methods. For example, a popular one is [sentiment analysis](https://en.wikipedia.org/wiki/Sentiment_analysis).

Another topic to look into is category theory. If you want to build purely theoretical mathematical models of social phenomena, that's probably going to be the way to do it. E.g. [a paper where they did just that](https://www.sciencedirect.com/science/article/pii/0010028580900146).

So yes, there are many reasons theoretical computer science is important in the social sciences, and we are just beginning to understand how they can inform each other. This is an exciting time to be in your position!

EDIT: Fixed the link, thanks Damiano Mazza!

> **Comments:**
> **username_6**: I'm not very familiar with category theory. Could you elaborate what the advantage of the language of category theory is for social sciences over the language of graph theory?  
> **username_8**: @Discretelizard: The premise of your question is misguided; category theory is not an alternative to graph theory. In this context, its main benefit of it is that it gives a uniform language for expressing constructions from game theory, automata theory, control theory, and spectral graph theory, and furthermore this language is amenable to analysis using linear-algebraic techniques  (i.e., what category theorists call monoidal categories). It's the **same** techniques, but expressed in a way which generalises more easily.  
> **username_6**: @NeelKrishnaswami I see. Perhaps it would have been more correct to ask what category theory can give us in this context that graph theory cannot. Nevertheless, you answered my question.  
> **username_9**: I do think that category theory has the potential to offer interesting perspectives for linking social sciences and computer science.  However, judging from the abstract (I do not have access to the full paper, unfortunately) the link given as an example of the application of category theory to social sciences does not seem to contain any category theory at all (also, when I read "recent paper" I expected something more recent than 2007, but that's subjective :-) ).  Maybe there's a mistake in the link?  
> **username_10**: I find it very hard to call the work done by the names you mentioned (Newman, Clauset, Christakis) TCS. These people are network scientists, by training some physicists, some computer scientists, some economists, etc. and they certainly do work on what's broadly considered "computational social science", but it's not TCS. Note, although network theory uses some graph theory, it actually relies a lot more on fields like statistical physics, and I'd be very surprised if I ever see a work I'd call TCS by a network theorist (I'm quite familiar with both field).  
> **username_10**: Also, computational social science is usually relatively applied, and A LOT less abstract than TCS. There is TCS work in social science, but mostly done in economic theory and micro economic theorists work on that. This might be also the only overlap in scholars (but I wouldn't say in research) between network science and TCS, e.g. Matthew Jackson.  

---

### Answer by username_11 on 2021-08-16. Score: 6

It seems to me that your best chance at applying TCS to social sciences is to apply it to study problems in economics. In particular, one can use TCS to argue that certain tasks required in economics are computationally infeasible. For a concrete example of this, see the following write-up:
<https://m-cacm.acm.org/magazines/2011/5/107705-computational-complexity-and-information-asymmetry-in-financial-products/fulltext#R5>

> **Comments:**
> **username_0**: Thanks for the advice, I appreciate it. Know the funny part? I'm actually looking at other fields like sociology/anthropology.  

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### Answer by username_12 on 2021-08-17. Score: 2

I used to study economics, and the answer is yes. In 2019/2020 Nobel Laureate Paul Milgrom gave the marshall lectures in cambridge with the title "Market Design When Resource Allocation is NP-Hard". I believe that there is plenty of intersection between game theory and TCS, (e.g., search algorithmic game theory books on amazon).

<https://www.econ.cam.ac.uk/Marshall_Lecture>


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### Answer by username_4 on 2021-08-16. Score: 1

"Stupid" is subjective and judgmental, but there are certainly meaningless, trivial, or uninteresting questions. Or at least sometimes they can *seem* meaningless until someone comes along and imbues them with meaning. Let's take math, for example. The search for the smallest positive real might have been meaningless before nonstandard analysis was discovered. Similarly, the search for an integer that's both even and odd might seem silly at first, but perhaps might actually make sense in some paraconsistent logic.

"Trivial" means easily solvable by anyone with a minimal set of commonly available tools, not a research question. "Uninteresting" means lacking a compelling motivation or structure. Number theory is famous for being able to generate endless problems not solvable by current techniques, and number theorists are rather picky about which ones they choose to devote time to. Their criteria, I imagine, include: which are the likeliest to be amenable to the tools we do have? Which hold the promise of shining light on new structure or leading to new tools and techniques?

Finally, I'll attempt an answer to the OP. A "stupid" question is one that the research community agrees, by broad consensus, is not a research question -- and is posed, as a research question, by someone who is in a position to know better.


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