As a PM, I'd support it as an A/B test. Show some percentage of your users an increased level of posts from the opposite party, some others an increased level of posts from their own party, and leave the remaining 90% alone. After running that for a month or two, see which of those groups is doing better.
They've clearly got something interesting and possibly important, but 'interaction strength' is not intrinsically good or bad. I would instead ask the researcher to pivot from a metric of "interaction strength" to something more closely aligned to the value the user derives from their use of your product. (Side note: Hopefully, use of your product adds value for your users. If your users are better off the less they use their platform, that's a serious problem).
Do people interacting with posts from the opposite party come away more empathetic and enlightened? If they are predominantly shown posts from their own party, does an echo chamber develop where they become increasingly radicalized? Does frequent exposure to viewpoints they disagree with make people depressed? They'll eventually become aware outside of the discussion board of what the opposite party is doing, does early exposure to those posts make them more accepting, or does it make them angry and surprised? Perhaps people become fatigued after writing a couple angry diatribes (or the original poster becomes depressed after reading that angry diatribe) and people quit your platform.
Unfortunately, checking interaction strength through comment word counts is easy, while sentiment analysis is really hard. Whether doing in-person psych evals or broadly analyzing the users' activity feed for life successes or for depression, you'll have tons of noise, because very little of those effects will come from your discussion board. Fortunately, your brilliant data scientist is brilliant, and after your A/B test, has tons of data to work with.
They've clearly got something interesting and possibly important, but 'interaction strength' is not intrinsically good or bad. I would instead ask the researcher to pivot from a metric of "interaction strength" to something more closely aligned to the value the user derives from their use of your product. (Side note: Hopefully, use of your product adds value for your users. If your users are better off the less they use their platform, that's a serious problem).
Do people interacting with posts from the opposite party come away more empathetic and enlightened? If they are predominantly shown posts from their own party, does an echo chamber develop where they become increasingly radicalized? Does frequent exposure to viewpoints they disagree with make people depressed? They'll eventually become aware outside of the discussion board of what the opposite party is doing, does early exposure to those posts make them more accepting, or does it make them angry and surprised? Perhaps people become fatigued after writing a couple angry diatribes (or the original poster becomes depressed after reading that angry diatribe) and people quit your platform.
Unfortunately, checking interaction strength through comment word counts is easy, while sentiment analysis is really hard. Whether doing in-person psych evals or broadly analyzing the users' activity feed for life successes or for depression, you'll have tons of noise, because very little of those effects will come from your discussion board. Fortunately, your brilliant data scientist is brilliant, and after your A/B test, has tons of data to work with.