@inproceedings{tigunova-etal-2020-reddust,
    title = "{R}ed{D}ust: a Large Reusable Dataset of {R}eddit User Traits",
    author = "Tigunova, Anna  and
      Mirza, Paramita  and
      Yates, Andrew  and
      Weikum, Gerhard",
    editor = "Calzolari, Nicoletta  and
      B{\'e}chet, Fr{\'e}d{\'e}ric  and
      Blache, Philippe  and
      Choukri, Khalid  and
      Cieri, Christopher  and
      Declerck, Thierry  and
      Goggi, Sara  and
      Isahara, Hitoshi  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Mazo, H{\'e}l{\`e}ne  and
      Moreno, Asuncion  and
      Odijk, Jan  and
      Piperidis, Stelios",
    booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
    month = may,
    year = "2020",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://preview.aclanthology.org/ingest-emnlp/2020.lrec-1.751/",
    pages = "6118--6126",
    language = "eng",
    ISBN = "979-10-95546-34-4",
    abstract = "Social media is a rich source of assertions about personal traits, such as ``I am a doctor'' or ``my hobby is playing tennis''. Precisely identifying explicit assertions is difficult, though, because of the users' highly varied vocabulary and language expressions. Identifying personal traits from implicit assertions like I{'}ve been at work treating patients all day is even more challenging. This paper presents RedDust, a large-scale annotated resource for user profiling for over 300k Reddit users across five attributes: profession, hobby, family status, age,and gender. We construct RedDust using a diverse set of high-precision patterns and demonstrate its use as a resource for developing learning models to deal with implicit assertions. RedDust consists of users' personal traits, which are (attribute, value) pairs, along with users' post ids, which may be used to retrieve the posts from a publicly available crawl or from the Reddit API. We discuss the construction of the resource and show interesting statistics and insights into the data. We also compare different classifiers, which can be learned from RedDust. To the best of our knowledge, RedDust is the first annotated language resource about Reddit users at large scale. We envision further use cases of RedDust for providing background knowledge about user traits, to enhance personalized search and recommendation as well as conversational agents."
}