Hanna Wallach published a thought piece of what computational social science is, especially from her computer science point of view. Given computational social science in mind, She made points of differences between computer science and social science in terms of goals, models, data, and challenges:

  •  Goals: Prediction vs. explanation — “[C]omputer scientists may be interested in finding the needle in the haystack—such as […] the right Web page to display from a search—but social scientists are more commonly interested in characterizing the haystack.”
  • Models: “Models for prediction are often intended to replace human interpretation or reasoning, whereas models for explanation are intended to inform or guide human reasoning.”
  • Data: “Computer scientists usually work with large-scale, digitized datasets, often collected and made available for no particular purpose other than “machine learning research.” In contrast, social scientists often use data collected or curated in order to answer specific questions.”
  • Challenges: Datasets consisting of social phenomena raised ethical concerns regarding privacy, fairness, and accountability — “they may be new to most computer scientists, but they are not new to social scientists.”


She concludes her article saying that “we need to work with social scientists in order to understand the ethical implications and consequences of our modeling decisions.”

The article is available here.