All kinds of economists estimate models on very large data using computers. Does that count or not?
What good is it specifically to “know habermas as well as feature selection” ? What problems are you solving?
Maybe “the world needs an explanation of what you mean when you say computational social science” would make a nice follow up…
I gathered the quote is not about Habermas and feature selection per se, but a platitude about bridging theory and practice--both social and computational theories and practices. Knowing when, for instance, not to divvy up social features that may constitute a larger (digital) public, or conversly combining/throwing away features that may in fact constitute multiple publics or subject groupings, paves the way for building more accurate or generalisable computational social science models.
Why would we want such models? Perhaps to map 'hunches' about social life that were previously only in the realm of rhetoric or simply too difficult to map before the advent of large scale data collection and computation.
https://sph.umich.edu/faculty-profiles/anthony-denise.html
One of the things we did was build survey apps for phones which would sense activity and only pop up a question when a person wasn't doing much. The sensor data would also serve as a ground truth, telling us for example how much activity a person really did, versus how much they think they did. One early result from such research was that people think they are always doing things, rushing around, when the truth is they are sitting doing little for 95% to 99% of the day. We used the survey app to build a system to train a gait recognition machine learning algorithm for user authentication, where the survey app collected both sensor data and quick answers about what a person thought they were doing, where they were, were they walking, where they were... A lot of todays AI projects are essentially computational sociology, algorithms trained on peoples behavior that is used for predictions.
Business has bought up a lot of the sociology talent, to work with marketing, motivating employees, and changing peoples minds (somebody had to design those motivational posters in the hallways and some of them were based on sociology, lobbying campaigns to change public opinion are based on sociology, political campaigns use sociologists work).
I have a strong suspicion that all the Big Tech companies that collect lots of intimate data about people are employing sociologists to analyze that data and use it for many purposes, mostly related to advertising and motivating people to buy stuff, but also swaying opinion, making market decisions, investing, hiring and firing, and more. A common refrain in economics is that markets are unpredictable because you can't know what all the individual players are thinking, well now you can measure them and build models/AI. Big computational social science already exists at scale. I wonder what is being done with the health data from fitness trackers.
Similar things have been happening in economics. Unfortunately in both cases the data is being used mainly to gain special private knowledge about the social behavior of people, rather than informing the public or public policy. Because money. There are a few researchers who are more interested in the public good though.
No need for speculation Facebook got caught experimenting on their users to see the impact of the news feed on their emotional state:
https://www.theguardian.com/technology/2014/jun/30/facebook-...
At the moment, social science is an oxymoron.
From this point of view, Sozialwissenschaften is less the act of pinpointing universals, but rather engaging with the plurality of social life and knowledge making.
Are they still useful? Yes, they still give us a needed picture. However, until we can build a near perfect simulation of the world at the atomic level, social studies will be likely remain as an alchemy or astrology instead of a chemistry or astronomy. There are just too many variables not being accounted for and they depend on too many other disciplines that are also still relatively young like computer science and chaos theory.
Hence why I brought up the difference and why I think language differences are important--the ways in which scientists, academics and researchers understand practices of knowing and knowledge building informs their scientific process and the models of reality they hold as true. Besides, models frequently 'drift' and are rarely cut and dry[0], just as blanketing all social science models as irreplicable is simply not true (see Lotka's Law or the Barabási–Albert model; statisticians contributing greatly to social science) [1][2].
More problematically, and not necessarily directed to your views alone, is the continued 'dunking' on 'non-scientific' disciplines. Why are humanist methods held to indefinite scrutiny, while similar criticism could as easily be directed elsewhere? For instance, dismissing physics as 'not a science' because models fail to predict quantum phenomena, mathematics as 'not a science' because there are limits to provability, machine learning as 'not a science' because source corpora are subjectively chosen, and so on (just examples, not my critiques of them).
It is precisely why I regard computational social science as important, seeking to bridge the seeming incompatibilities between exact and inexact phenomena. Even after more than a century of social science, we are only at the cusp of understanding the foundational patterns that make up social life, with contemporary computational methods and data collection capabilities offering new levels of detail into phenomena that were previously difficult to investigate.
[0]: https://en.wikipedia.org/wiki/Concept_drift
> It is precisely why I regard computational social science as important, seeking to bridge the seeming incompatibilities between exact and inexact phenomena.
Yes, this is what I meant with a near perfect simulation. We agree here
> Even after more than a century of social science, we are only at the cusp of understanding the foundational patterns that make up social life
This is what’s meant for social studies lacking repeatable theoretical models
In any case, the language example used here was more to demonstrate the historic and perceptual differences as to what amounts to science, and that for some social science is not necessarily an oxymoron.
Edit: wissenschaft and wetenschap are furthermore direct translations, while natural philopsophy moreso indicates a field or discipline (akin to 'Naturphilosophie' or 'wijsbegeerte'). While this can be regarded as 'just semantics', the categories are subtly different enough, at least to a second-language speaker.