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daveywoods
Joined: 07/08/1999
Posts: 2,387
Likes: 13
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AI on TSL. No kidding.

I'm working on a TSL AI, just for fun. I ran this by Will, he said OK. I'm trying to build a sentiment analysis tool to evaluate TSL message board posts for Positive, Negative, or Neutral. If it works, I'll give it to TSL (or I'll run it for TSL). It will be interesting to see how message board sentiment trends through the season. This would be run on the bulk of the board, not labeling individual messages. Something like "this week the message board is 63% more positive than last week". This is achieved by grading individual messages, but only aggregate data would be reported. But assessment of positive or negative is obviously a subjective evaluation, which is why I'm here asking for help. I'm looking for people to "grade" the AI training data. That means looking at a few hundred rows of data and marking them as positive, negative, or neutral. The way AI works, if we give it human input on some data, it will be able to go ahead on an automated basis. If I train all the data myself, the sentiment analysis will be skewed by my bias. And anyway I could use help looking at all this data. If you're interested, email me and I'll send you 300 rows of messages to look at. You can do as many or as few as you like. This is simply looking at the data I have pulled off the message board for subject line and message, and grading that message as positive, negative, or neutral. Please help if this absurd nerdery interests you. my email address is my username at gmail dot com. Also I should mention -- Pretty good chance this never works, but let's try. It's neat.
Posted: 03/22/2024 at 09:02 PM ET

Thread Replies (14)

Full Thread →
AI on TSL. No kidding.
daveywoods 03/22/24 09:02 PM ET
TSL message boards skewed? Impossible**
Hokie1992 03/25/24 04:00 PM ET
What are you writing this text classifier in? Using pytorch or something…
csHokie04 03/24/24 10:01 PM ET
Scikit-Learn to split the data in Jupyter Notebook**
daveywoods 03/26/24 04:39 PM ET
I'll bet it's often negative. Only because negative comments are >>> +
CPVT3 03/24/24 12:35 PM ET
Interested
949hokie 03/24/24 01:17 AM ET
"Hal, open the portal bay doors."**
KCHokie2 03/23/24 11:00 PM ET
Up till now, this kind of effort has always failed
WestyHokie 03/23/24 06:32 PM ET
I grade this post as Negative ;)
jesuisvtguy 03/23/24 12:52 PM ET
I can rank all of the posts from Phew, Bama and Johnny Hawk. Done.**
dolph 03/23/24 11:22 AM ET
It's hard to characterize sarcasm/snark as 'positive' or 'negative'.
The_Phew 03/23/24 12:09 PM ET
I'll take Pogo or L'il Abner, thank you**
TomTurkey 03/24/24 07:35 PM ET
That's why AI models are trained, they are taught who the snarks are ;)**
Vienna_Hokie 03/23/24 02:44 PM ET
Train the model with Reddit, and 'no snark' would be considered negative.
The_Phew 03/24/24 01:04 PM ET
Happy to help. I’m very good at gauging
Pride_and_Joy 03/22/24 10:28 PM ET