I also found the DrL helpful in the context of my post above, it clearly indicated those who posted once to an introduction thread and were never heard from or interacted with again.
Course leaders are likely to have high in-degree because in-degree can be understood as a proxy for prestige or popularity within the network. People are mentioning, RTing, replying to posts. Even if course leads and big names tweet less, those tweets/nodes are amplified via RT and mentions, so you get leaders who have low out-degree (not too many contributions) and high in-degree (lots of attention from the network).
In a study (Gilbert & Paulin, 2015) on expertise and centrality in acadmeic conference Twitter networks and their propensity to support learning, we looked into whether the 'experts' of the conference had high levels of centrality, prestige, tweeted more or less than non-experts, and would be frequently mentioned in network tweets. We found that experts were likely to have high centrality vs non-experts, were retweeted significantly more frequently than non-experts, and mentioned significantly more than non-experts. Tweet frequency (we thought it would be lower than non-experts) was not associated with expertise, some tweeted a lot, others didn't.
I also think it would be interesting to dig further into why outdegree is so much higher than indegree for most within this network; I imagine that it is the same for most networks as only a few people gain the popularity/prestige of lots of mentions and RTs across 'discussions' network wide, even though there may be good dialogue going on throughout the network between smaller in-groups.
On reciprocity at the node level - will let someone else speak to this, as it's an interesting point and I honestly don't know the answer off hand. I do know in M. Hawksey's TAGSExplorer tool, there is a ranking of 'top conversationalists' in the network viz - I had always assumed (but honestly should look into it further to see if I'm correct) it was something similar to this: does a node have lots of two way ties?
Gilbert, S., & Paulin, D. (2015, January). Tweet to learn: Expertise and centrality in conference Twitter networks. In System Sciences (HICSS), 2015 48th Hawaii International Conference on (pp. 1920-1929). IEEE. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7070042