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Rank aggregation is a fundamental task in social choice theory. Given a collection of different rankings (total orders) over the same set of objects, the goal is to produce a single ranking of those objects that, in some way, aggregates the different opinions expressed by the input rankings.

Rank aggregation has applications in many fields. For example, in biological research, several research methods may produce different rankings of objects (e.g., genes), and it is desirable to combine these into a single ranking. See^[1] for a survey of rank aggregation methods in biological contexts.

The Kemeny method is a commonly used approach to rank aggregation. It selects an output ranking that minimises the sum of Kendall tau distances to all input rankings. It is considered majoritarian in the sense that if more than 50% of the input rankings are identical, then the method will necessarily return that ranking.

However, in some contexts it may be desirable to aggregate rankings in a more proportional manner that also takes minority rankings into account. A related rule, sometimes referred to as the squared Kemeny method, minimises the sum of squared distances. This approach guarantees an upper bound on the distance between the output ranking and any input ranking, depending on its frequency in the input.^[2]

• Ranked voting – a setting in which the input consists of rankings of candidates, and the goal is to select a single candidate or a subset of candidates rather than produce a full ranking.
• Arrow’s impossibility theorem – a fundamental result in social choice theory concerning the limitations of ranked voting systems.
• Social welfare function – a function that takes individual preferences as input and produces a collective ranking of alternatives.