Understanding the key trends on the house market using topic modeling tool on relevant Twitter texts -- 2

My firm is a real estate company and we see out of the 10 clients coming in, only 2 make a final purchase. Hence we need to understand why potential clients does not make the final decision so that we can work on a proactive marketing plan. For this project,

- Pull data from twitter with relevant hashtags like @john pasalis,
- Collect the data, clean the data, preprocess the data,
- Run sentiment analysis to separate the negative subset texts
- Create a topic model on the negative sub set of data and fine tune the topics
- Create keygraph of the topics

The skillset required are

- Python
- Twitter API
- Anaconda
- Pycharm