In past years several works have noted that Twitter data are essential in diverse fields and may have a lot of applications. Nevertheless, the API proposed by Twitter sternly restricts access to public data generated by users. These restrictions have the consequences of greatly slowing down the contributions of researchers and of limiting their scope. In this paper we introduce TwiScraper, a collaborative project to enhance Twitter data collection by scraping methods. We present a module allowing user-centered data collection: Twi-FFN.