I have been collecting the number of new followers every day for about 6 months for 30 different twitter accounts and I know the exact time that they started following. I have been also collecting all tweets for these accounts during this time period.
I'm interested in whether some independent variables (tweet rate, number of mentions, retweets, links, sentiment of the tweets) are related to an increase in followers (or the dependent variable.)
I'm wondering what the appropriate approach is for this time series data.
For example, I could use linear regression to see if the total amount of tweets per day predict the amount of new followers per day. However, I don't think that would be appropriate because actions people take don't immediately affect the number of followers. But I'm not sure what the time delay would be or if there is a different approach that would be more appropriate for this kind of data and the question I am asking. I am using R.