I have the following data at hand:
- data about internet usage, per hour, per user, per part of the day (morning, afternoon, evening);
- the category of websites visited and their duration;
- demographic information about the users;
- (basically all surfing information that you can think of is available).
I have 1000 users with their corresponding data for 24 months. Approximately a total of 24 x 1000 data points (per user per month).
I am trying to predict the trend of web surfing for a group (not an individual), for about 6 months ahead in time, based on several demographic and historical features. I could just plot the surfing duration for porn websites over time for teenagers and call it a trend, but I also need to take into account the impact of other features.
I earlier thought of this as a regression problem, but I realised that I could only predict for a given user at a particular point in time, based on historical data. This wouldn't give me a surfing trend for categories or age groups.
How can I find such trends for a category (e.g., adults and porn) based on other demographic information.
How can I see the interactions between the variables? What is the approach or the models I should look at?