Background. The risk of infection from respiratory pathogens increases according to the contact rate between the infectious case and susceptible contact, but the definition of adequate contact for transmission is not standard. In this study we aimed to identify factors that can explain the level of contact between tuberculosis cases and their social networks in an African urban environment. Methods. This was a cross-sectional study conducted in Kampala, Uganda from 2012-2016. We carried out an exploratory factor analysis (EFA) in social network data from tuberculosis cases and their contacts. We evaluated the factorability of the data to EFA using the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO). We used principal axis factoring with oblique rotation to extract and rotate the factors, then we calculated factor scores for each using the weighted sum scores method. We assessed construct validity of the factors by associating the factors with other variables related to social mixing. Results. Tuberculosis cases (N = 120) listed their encounters with 1,154 members of their social networks. Thirteen variables displayed high inter-correlation (KMO=0.72) and were included for EFA. Two factors were identified, which captured 82% of the variance. The first factor, named ‘Setting’, involves the type, frequency, duration and ventilation of the usual place of meeting as well the physical proximity among tuberculosis cases and contacts, represented by the sleeping and eating patterns. The second factor, named ‘Relationship’, was explained by the relationship, its duration, and the level of intimacy among cases and contacts, represented by the strength of knowledge of each other, provision of healthcare, and whether they were travel partners. Setting and Relationship scores varied according to the age, gender and nature of the relationship among tuberculosis cases and their contacts. Conclusions. In this large cross-sectional study from an urban African setting, we identified two factors that can assess adequate contact between tuberculosis cases and their social network members. These findings also confirm the complexity and heterogeneity of social mixing.