Section: New Results

Applications in Social Networks

Participants : Eitan Altman, Swapnil Dhamal, Giovanni Neglia.

Utility from accessing an online social network

The retention of users on online social networks has important implications, encompassing economic, psychological and infrastructure aspects. In the framework of our joint team with Brazil (Thanes), G. Neglia, together with E. Hargreaves and D. Menasche (both from UFRJ, Brazil) investigated the following question: what is the optimal rate at which users should access a social network? To answer this question, they have proposed an analytical model to determine the value of an access (VoA) to the social network. In the simple setting they considered, VoA is defined as the chance of a user accessing the network and obtaining new content. Clearly, VoA depends on the rate at which sources generate content and on the filtering imposed by the social network. Then, they have posed an optimization problem wherein the utility of users grows with respect to VoA but is penalized by costs incurred to access the network. Using the proposed framework, they provide insights on the optimal access rate. Their results are parameterized using Facebook data, indicating the predictive power of the approach. This research activity led to two publications in 2019 [49], [43].

Last year, the same researchers, together with E. Altman, A. Reiffers-Masson (IISc, India), and the journalist C. Agosti (Univ of Amsterdam, Netherlands), have worked on Facebook News Feed personalization algorithm. The publication [21] complete that line of work described in Neo 's 2018 technical report.

Optimal investment strategies for competing camps in a social network

S. Dhamal, W. Ben-Ameur (Telecom SudParis), T. Chahed (Telecom SudParis), and E. Altman have studied the problem of optimally investing in nodes of a social network in [17], wherein two camps attempt to maximize adoption of their respective opinions by the population. Several settings are analyzed, namely, when the influence of a camp on a node is a concave function of its investment on that node, when one of the camps has uncertain information regarding the values of the network parameters, when a camp aims at maximizing competitor's investment required to drive the overall opinion of the population in its favor, and when there exist common coupled constraints concerning the combined investment of the two camps on each node. Extensive simulations are conducted on real-world social networks for all the considered settings.

S. Dhamal, W. Ben-Ameur (Telecom SudParis), T. Chahed (Telecom SudParis), and E. Altman have studied a two-phase investment game for competitive opinion dynamics in social networks, in [18]. The existence of Nash equilibrium and its polynomial time computability is shown under reasonable assumptions. A simulation study is conducted on real-world social networks to quantify the effects of the initial biases and the weigh attributed by nodes to their initial biases, as well as that of a camp deviating from its equilibrium strategy. The study concludes that, if nodes attribute high weight to their initial biases, it is advantageous to have a high investment in the first phase, so as to effectively influence the biases to be harnessed in the second phase.

Extending the linear threshold model

S. Dhamal has proposed a generalization of the linear threshold model to account for multiple product features, in [38]. An integrated framework is presented for product marketing using multiple channels: mass media advertisement, recommendations using social advertisement, and viral marketing using social networks. An approach for allocating budget among these channels is proposed.

Public retention in Youtube

There exist many aspects involved in a video turning viral on YouTube. These include properties of the video such as the attractiveness of its title and thumbnail, the recommendation policy of YouTube, marketing and advertising policies and the influence that the video’s creator or owner has in social networks. E. Altman and T. Jimenez (CERI/LIA, Univ Avignon), study in [29] audience retention measurements provided by YouTube to video creators, which may provide valuable information for improving the videos and for better understanding the viewers’ potential interests in them. They then study the question of when is a video too long and can gain from being shortened. They examine consistency between several existing audience retention measures. They end in a proposal for a new audience retention measure and identify its advantages.

The medium selection game

F. Lebeau (ENS Lyon), C. Touati (Inria Grenoble-Rhone-Alpes), E. Altman and N. Abuzainab (Virginia Tech, USA) consider in [45] competition of content creators in routing their content through various media. The routing decisions may correspond to the selection of a social network (e.g. twitter versus facebook or linkedin) or of a group within a given social network. The utility for a player to send its content to some medium is given as the difference between the dissemination utility at this medium and some transmission cost. The authors model this game as a congestion game and compute the pure potential of the game. In contrast to the continuous case, they show that there may be various equilibria. They show that the potential is M-concave which allows them to characterize the equilibria and to propose an algorithm for computing it. They then introduce a learning mechanism which allows them to give an efficient algorithm to determine an equilibrium. They finally determine the asymptotic form of the equilibrium and discuss the implications on the social medium selection problem.