analysis.attendance

bigbang.analysis.attendance.name_email_affil_relations_from_IETF_attendance(meeting_range=[106, 107, 108], threshold=None)

Extract and infer from IETF attendance records relations between full names, email address, and affiliations.

In the returned dataframes, each row represents a relation between two of these forms of entity, along with the maximum and minimum date associated with it in the data.

Two forms of inference are used when generating these relational tables:

• Missing values in time are filled forward, then filled backward

• TODO: Affiliations are ran through the entity resolution script to reduce them to a ‘cannonical form’

Parameters

• meeting_range (list of ints) – The numbers of the IETF meetings to use for source data

• threshold (float) – Defaults to None. If not None, activate entity resolution on the affiliations. Threshold value is used for the entity resolution.

Returns

• rel_name_affil (pandas.DataFrame)

• rel_email_affil (pandas.DataFrame)

• rel_name_email (pandas.DataFrame)