BACKGROUND

Websites and online social networks, such as Twitter, Facebook, and discussion boards, have become some of the most popular places where controversial arguments are held. Accordingly, technological tools have also become important in shaping these discussions by curating and filtering the content seen by each user. From a computational perspective, however, controversy has not been understood well enough. Algorithms based on an incomplete understanding of controversy are bound to fail in unexpected ways, which can replicate or even exacerbate the sources of human bias.

SUMMARY

Disclosed herein are systems and methods that can address these issues by modeling controversy as a combination of at least “contention” and “importance” with respect to a given population.

One example embodiment is a system for modeling controversy within a population. The example system includes an interface, memory, and processor. The interface is configured to obtain information regarding stances of individuals in the population on a topic. The processor is configured to determine, and store in the memory, a representation of contention on the topic among individuals of the population, the representation of contention being based on the stances of individuals in the population. The processor is further configured to determine, and store in the memory, a representation of importance of the topic within the population. The processor is configured to create, and store in the memory, a model of controversy for the topic based on the representations of contention and importance.

Another example embodiment is a method of modeling controversy within a population. The example method includes determining contention on a topic among individuals of the population, determining importance of the topic within the population, and creating a model of controversy for the topic based on the contention and importance.

Another example embodiment is a machine-readable storage medium having stored thereon a computer program for modeling controversy within a population. The computer program includes a routine of set instructions for causing the machine to determine contention on a topic among individuals of the population, determine importance of the topic within the population, and create a model of controversy for the topic based on the contention and importance.

The topic or the stances can be expressed in any of: textual information, numeric data, survey responses, blog post, article comment, webpage, social media post, online forum post, any combination thereof, or any other online or offline data sources. The disclosed systems and methods can predict whether the topic is controversial based on the model of controversy, and can determine a controversy score for the topic based on the model of controversy. In some embodiments, determining contention on the topic can include determining a proportion of individuals in the population that are in disagreement regarding the topic. In some embodiments, determining contention can include determining stances that individuals in the population have on the topic, and can include determining a probability that two given individuals have conflicting stances on the topic. In some embodiments, it can be determined whether pairs of stances are mutually exclusive, thus reducing complexity of the determination of controversy. In some embodiments, determining importance of the topic can include determining a probability that the topic is importance to a given individual in the population.

Another example embodiment is a system for determining contention within a population. The example system includes an interface, memory, and processor. The interface is configured to obtain information regarding stances of individuals in the population on a topic. The processor is configured to determine, and store in the memory, representations of stances of individuals in the population with regard to a topic. The processor is further configured to, for pairs of stances, determine, and store in the memory, a representation of a measure of conflict between a first stance and a second stance. The processor is further configured to determine, and store in the memory, a representation of a probability that a first individual and a second individual hold conflicting stances on the topic.

Another example embodiment is a method of determining contention within a population. The example method includes determining stances of individuals in the population with regard to a topic. For pairs of stances, a measure of conflict can be determined between a first stance and a second stance. The example method further includes determining a probability that a first individual and a second individual hold conflicting stances on the topic.

Another example embodiment is a machine-readable storage medium having stored thereon a computer program for determining contention within a population. The computer program includes a routine of set instructions for causing the machine to determine stances of individuals in the population with regard to a topic. For pairs of stances, a measure of conflict can be determined between a first stance and a second stance. The computer program further includes instructions for causing the machine to determine a probability that a first individual and a second individual hold conflicting stances on the topic.

Determining a stance of an individual can include determining whether the individual holds a stance on the topic. For a plurality of stances, individuals holding a particular stance can be grouped into a stance group. In such embodiments, determining a probability that a first individual and a second individual hold conflicting stances on the topic can include determining a probability that a first individual and a second individual belong to conflicting stance groups. For a given stance group, individuals holding a mutually exclusive stance with respect to the given stance group can be grouped into an opposing stance group. In such embodiments, determining a probability that a first individual and a second individual hold conflicting stances on the topic can include determining a probability that a first individual belongs to a given stance group and that a second individual belongs to an opposing stance group with respect to the given stance group.

