I have set of users and the topics they discuss as follows.
User, Topic, Number_of_times_discussed Jone, movies, 3 Emi, food, 6 Jenne, movies, 1 Ej, tv series, 2 Micheal, tech, 8 Jone, comedy, 1
I also got another list that describes how interesting the topic was to the listeners. This
interestingness score is in the range of
0-1. Note that some topics do not have interestingness score provided in the dataset (e.g.,
Topic, Interestingness_score movies, 0.9 food, 0.1 tvseries, 0.6 tech, 0.8
Now, I want to have a weighted score for each connection that the users have with topics based on the two values I have. The first method I tried was as follows (see
User, Topic, Number_of_times_discussed, weighted_score Jone, movies, 3, 3+(3*0.9) Emi, food, 6, 6+(6*0.1) Jenne, movies, 1, 1+(1*0.9) Ej, tv series, 2 2+(2*0.6) Micheal, tech, 8 8+(8*0.8) Jone, comedy, 1 1+(1*0) <- since I do not have a interestingness_score for comedy
However, I would like to know if there are more statistical ways to induce the
intrestingness_score for each connection to weight them. I am happy to provide more details if needed.