There are so many ways to do it... Do you need this data for yourself, or you are planning to make a product around it?

From what I see you can use Twitter API and Facebook Graph API (Are you comfortable programming?) Most of the students are active on social media so you will find lots of data. Facebook graph API will give you a number of likes and comments to all the posts of you competitors. You can analyze all the posts of your competitors. Using Twitter API you can get all the twits that use certain hashtags or mentions. If you are not into coding, but still want to get social media information, you can take a look at tools like IBM Watson ANalytics ($30 for personal use), it natively connects to Twitter API, and you don't have to be a programmer at all. It is intuitive and easy to learn. Analytics Canvas connects to Facebook Graph API (it's free for 30 days of trial).

Unfortunately, you would not be able to collect any personal information from social media at large scale (age, income, gender, etc.), because it violates all the laws about privacy on the Internet. You can use census data instead.

Google Sheets are a very handy tool if you are planning to use this information for personal research. You can set up a spreadsheet and add some Java script to make it collect all information from competitor's blogs, and also sites like Reddit.

Finally, you can try web scraping (it's not the best, but can speed up the process). A tool like OutWitHub will collect information from websites (such as website reviews) based on the structure you provide (select html tags). You can collect thousands of reviews in one day if you automate it (paid version). Very easy to use.

Note: not all the websites are open to this method, review their policies to make sure you are not violating their terms of service. Reviews belong to the website where they were published.

If you REALLY need personal data (like how much they earn and how much they spend, etc.), just print out 100 questionnaires and go to Student Union Building of Dalhousie University. Most of the students will share any personal data in exchange for a Tim Horton's gift card that gets them a free coffee. It is probably the least technical and fastest way to get all the data you need.

Hope this helps.

This one is tricky because all social media platforms have terms and site rules around collecting personal data. Facebook in particular is touchy about this, so I would not recommend it. Twitter has an API (https://developer.twitter.com/en/docs/tweets/search/overview) that will give you raw data for a small cost, so your hashtag information can be obtained that way. If you are serious about this, then I would identify the top 50-100 businesses that employ students in the area which also keep their pay scale in the range you're looking for. Then using those company's social media pages to identify employees. You are now zeroed on your audience, you just need to fine tune it to filter on the those students that eat out, perhaps by cross referencing Yelp/Google reviews with the employee data obtained.

I would like to re-emphasize here that this sort of data is tricky to obtain as many of the sites containing this data have terms and conditions which discourage collecting personal data.

Are you hoping for a dynamic system that identifies new data sources as they become available? Or will you identify existing sites/pages that give you the data you want and focus on what is generated there? From there, you can obtain the data manually or programatically. Manually, you will actually be visiting those pages on a regular basis, copying and pasting the data there, and then formatting the data to be usable. This is not a scalable solution, but can work if the data sources are limited and you've got the time. Programmatically, you can build small scripts that will make the site requests for you. If you don't program, there are many freelancers/developers that have this skillset and are reasonably priced. There are also 3rd party platforms that are well priced for small scale web crawling.
To sum up, you need to identify where you'll get your data from online (the income data & personal will be the trickiest), then identify how you want to obtain that data (manually or programmatically), and finally format the data into a usable dataset (CSV & JSON being simple and universal).

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