You can't ask people to cite things here. You'll get reprimanded!
/s
Yeah, I do believe Tesla is in the wrong here, but I don't think there's a whole lot anyone can or will do about it that will result in anything positive at this point.
The loudest in the thread will keep the noise level high, pushing all manner of imagined legal issues, unfortunately. At some point I'll have to stop wasting time here (either from being banned, or actually needing to do other things)... but for the moment I'd prefer the noise makers not win the day.
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O/T: Fun stats I compiled about this thread as of this post (yes, I wasted time on this while waiting on a firmware update issue):
- The user with the most posts in this thread has 1,717 posts in this thread alone... almost 13% of the thread. (Good lord...)
- The top two users in the thread make up nearly a full 20% (1 in 5) posts in the thread.
- Top top few users were not who I figured they'd be...
- I'm actually only the #22 poster by count in this thread with 137 posts, just over 1% of the thread (but #6 ranked by positive ratings count).
- The user with the most dislikes has 3x more than the #2 user (I'm actually #6 for dislikes thanks to only 3 users, only 2 of which are in the top 30 for posts here).
- Coincidentally, the user with the most dislikes has the most positive ratings as well. (Eliminating ratings from only the same 3 users as noted above drops them out of the top 30 for positive ratings, however... lol)
- 485 unique users have posted at least once here.
- 146 users have posted 10 or more times here.
- 46,169 ratings have been given to posts in this thread (43,094 were not "dislikes")
- Edit: Forgot to add some fun word counts:
- update: 3,728 mentions
- warranty: 3501 mentions
- voltage: 2755 mentions
- NHTSA: 1,091 mentions
- EPA: 706 mentions
- condition z: 397 mentions
- lawsuit: 541 mentions
- 4.2 volts: 149 mentions
- dieselgate: 137 mentions
- condition x: 129 mentions
Tons of other cool data. It's definitely pretty clear who makes noise and who contributes when you do some basic parsing and analysis of the data. For example, using post count vs ratings, combined with recursively weighting and balancing ratings from, for example, users who continuously give positive or negative ratings to the same people (regardless of the ratings of others), you basically get a list of users weighted by merit, and a second list of clear troublemakers. lol.