There has been an explosion in research into social media over the last decade, as you might expect. In a new article published in the Journal of Economic Literature (ungated earlier version here), Guy Aridor (Northwestern University), Rafael Jiménez-Durán (Bocconi University), Ro’ee Levy (Tel Aviv University), and Lena Song (University of Illinois Urbana–Champaign) document the trend. Here's Panel A of Figure 1 from the paper:
The increase in published research is clear (the "General interest publications" they refer to are more-or-less the top general journals in economics). Aridor et al.'s article reviews this large and growing literature, highlighting what is already known about the economics of social media, as well as where they see gaps suitable for future research. The focus of the review is often narrowed to a case study related to social media and politics, which while important in itself, is not the only important factor associated with social media. So, there may be additional research opportunities outside of those that are identified in the review.
Aridor et al. define social media as "two-sided platforms that primarily host user-generated content distributed via algorithms, while allowing for interactions among users". They then structure their review to follow the "flow of content" in social media, starting with content production (generated by users), then content distribution (including both 'organic content' and advertising, distributed by platforms using algorithms), and finally content consumption (again, by users).
The review is difficult to summarise, so if you are interested, I encourage you to read it in detail. In this post, I just want to highlight some of the research opportunities in this space (but not all of the opportunities that Aridor et al. describe - I'll focus on what I think are the more important or interesting ones).
First, in terms of content production, Aridor et al. note that:
...content creation is increasingly viewed as a viable career or income source... A natural next step to the existing evidence on the elasticity of the content supply curve concerns the labor economics of this activity, studying questions such as the effects of unions for content creators or whether monetary incentives crowd out nonmonetary motives. Beyond ad revenue–sharing programs, other monetary incentives that have been increasingly used by platforms (for example, allowing users to subscribe to producers) remain understudied, perhaps due to missing data.
Also:
More research is needed on how social media algorithms could affect the production of other types of content beyond news. For example, it has been argued anecdotally that TikTok is driving songwriters to focus on brief, danceable 15-second snippets.
In general, TikTok has probably been under-studied relative to other platforms, particularly given its large user base. Turning to misinformation, Aridor et al. note that:
The literature has mostly focused on the sharing, as opposed to the production, of misinformation. One potential reason for this imbalance is the role of resharing in diffusing misinformation... An important gap in this literature is to understand the determinants of the production of misinformation, beyond the sharing of existing articles.
And on fact-checking (which may now be more difficult to research given that Meta is giving up on fact checking):
One gap in this literature is to disentangle a potential dual role of fact-checking interventions, which affect not only the users’ perceived veracity of the content they are about to share but also the perceived likelihood that they will be fact-checked by the platform in the future.
Aridor et al. then turn to sanctions on users, and note that:
Besides crowd-sourcing, platforms conduct other content moderation measures at scale, such as down-ranking or removing posts, banning groups, and suspending user accounts... However, more research is needed to understand the causal effects of these “harder” interventions on the production of misinformation and the mechanisms through which they operate, whether they crowd out fact-checking efforts by the users, and the net welfare effect of sanctions.
And on counter-speech to reduce the toxicity on platforms:
An open question is what determines the equilibrium provision of counterspeech and how to incentivize users to provide this public good (similarly to fact-checking).
Finally on content production, Aridor et al. note that:
More evidence is needed on the connection between content moderation and advertising. Specifically, there is limited research examining how content moderation influences advertisers and, conversely, how advertising dynamics influence content moderation decisions... more evidence is needed to understand the effect of hate speech and other types of content on user interactions with advertisements and whether content moderation policies can alleviate any potential negative effects.
There seem to be a number of promising research opportunities in the content distribution space (and that likely primarily relates to a lack of access to the algorithms, which is why these questions haven't already been answered). Specifically, Aridor et al. note that:
Future research could examine what drives demand for social media content and when and to what extent content consumption is driven by algorithms.
And importantly:
An open question is how social media algorithms can optimally increase social welfare and what government incentives can encourage them to do so.
That last question is a big one, with huge potential for policy impact. I would be very surprised if there weren't already concerted research efforts in that space. Also:
...more research is needed on how users decide which pages to follow (for example, the accounts of media outlets or politicians), since those pages may be driving segregation.
Then, turning attention back to advertising, Aridor et al. note that:
Economic analysis of advertising... posits that advertising primarily works through the following channels: shifting beliefs through information (for example, product awareness, attribute information) or directly shifting consumer preferences (for example, increasing affinity to the brand)...
Empirical research suggests several unique aspects of social media advertising where these mechanisms interact with the “social” aspect of social media.... more work is needed to understand the relative role of each of the different mechanisms for ad effectiveness and how they interact with both the increased targeting abilities and the social aspect of social media advertising.
And finally:
...such a large amount of money is spent on digital advertising in national election campaigns is puzzling and deserves additional research, since either these ads are more effective than current research indicates or researchers are wrongly inferring the objectives that campaigns pursue with these ads (for example, fundraising rather than voter persuasion).
That question relates to some of my own earlier (and most cited) research on the impact (or rather, non-impact) of the number of social media followers on politicians' chances of being elected (see here, or here for an earlier ungated version). Aridor et al. also note that:
One direction for future work, even for studying these issues within the United States, is to better understand the impact of these types of ads in local elections, which is precisely where we may expect that social media advertising could have a larger impact.
I can say that in some follow-up work on local elections in New Zealand, which we haven't published, there was no significant effect of social media (which didn't surprise us at all, given the earlier results in national elections I pointed to above).
Aridor et al. then discuss opportunities in researching content consumption, and note that:
There are several avenues for future research. First, given the complex and fast-evolving nature of social media consumption, descriptive evidence detailing consumption behavior would be valuable... Second, while existing research highlights self-control problems among American adults, it is policy relevant to quantify the extent of these problems in the younger population. Finally, future work could look within platforms and quantify how different design features influence what and how users consume. Certain features (for example, content format or algorithms) may exacerbate self-control problems... Defining the key product characteristics and quantifying their effect on consumer choice is an important step forward in understanding the welfare implications of consumption.
And importantly:
There is convincing evidence that social media use—particularly the exposure to toxic content—can lead to offline hate crimes...
There is also some evidence that government regulation akin to a Pigouvian tax can mitigate this externality... Additional research is needed to study whether these policies have unintended consequences such as the silencing of political dissidents. Lastly, future research could explore how content moderation affects other offline harmful actions besides violence (for example, self-harm)...
And finally:
There are several interesting directions for future work. The first is that given the large informational externalities from consumption... an unexplored question is not only to measure market power in terms of time spent, but also to think of media power as Prat (2018) does for traditional media. Of particular interest is understanding whether social media increases or decreases the media power of existing large media organizations. The second is to explore the implications of habit formation... for competition among social media platforms.
The overall takeaway from this review is that, while there is a large (and quickly growing) literature on the economics of social media, there is still substantial scope for future research that will have real policy and practical impact. I look forward to seeing many of these research questions addressed in the near future.
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