In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the volume of past interactions and the time that has elapsed since the past interactions affect the actors’ decision-making to interact with other actors in the network. Recently occurred events may have a stronger influence on current interaction behavior than past events that occurred a long time ago–a phenomenon known as “memory decay”. Furthermore, negative past events may have a longer lasting effect on future interactions than positive past events. In this section, parametric and semi-parametric methods are developed to study memory decay of past events as a function of their transpired time. The methods are used to study how past interactions affect future interactions from text messages among students.