Predicting Reciprocity in Social Networks

Abstract

Abstract-In social media settings where users send messages to one another, the issue of reciprocity naturally arises: does the communication between two users take place only in one direction, or is it reciprocated? In this paper we study the problem of reciprocity prediction: given the characteristics of two users, we wish to determine whether the communication between them is reciprocated or not. We approach this problem using decision trees and regression models to determine good indicators of reciprocity. We extract a network based on directed @-messages sent between users on Twitter, and identify measures based on the attributes of nodes and their network neighborhoods that can be used to construct good predictors of reciprocity. Moreover, we find that reciprocity prediction forms interesting contrasts with earlier network prediction tasks, including link prediction, as well as the inference of strengths and signs of network links.

Hashtags 2.0 - An Annotated History of the Hashtag and a Window to its Future

“…In general, users in social networking sites (e.g., Twitter) can follow any user on the platform without the requirement of that other user to reciprocate. The connections between users in a social network can therefore have different meanings (Cheng, Romero, Meeder and Klienberg, 2011). 33 By the same token, they are quite fluid because the conversations promoted through them frequently arise, become visible and disappear much faster than those happening within follower networks.…”

Social exchange in online social networks. The reciprocity phenomenon on Facebook

“…Rice [35] also found support for direct reciprocity in a study of 24 months of computer conference system use among 10 groups involving over 87,000 total network links. The problem of reciprocity prediction was studied by Cheng et al [9]. They extract a network based on directed @-messages sent between users on Twitter, and they find that differences in reciprocity can be related to the notion of status.…”

Ignorance Isn't Bliss: An Empirical Analysis of Attention Patterns in Online Communities

“…Within this context [1] consider the problem of reciprocity prediction and study this problem in a communication network extracted from Twitter. They essentially aim to predict whether a user A will reply to a message of user B by exploring various features which characterise user pairs and show that features that approximate the relative status of two nodes are good indicators of reciprocity.…”

“…They essentially aim to predict whether a user A will reply to a message of user B by exploring various features which characterise user pairs and show that features that approximate the relative status of two nodes are good indicators of reciprocity. Our work differs from [1], since we do not aim to predict who will reply to a message, but consider the problem of identifying posts which will start a discussion and predicting the length of discussions. Further, we focus on exploring idiosyncrasies in the reply behaviour of different communities, while the above work studies communication networks on Twitter without differentiating between individual sub-communities which may use Twitter as a communication medium.…”

“…1 Our study was facilitated through a two-stage approach that (i) differentiates between seed posts -i.e. thread starters on a community message board that got at least one reply -and non-seed posts -i.e.…”