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Open AccessArticle

Recommending Links to Control Elections via Social Influence

1
Gran Sasso Science Institute, 67100 L’Aquila, Italy
2
ISI Foundation, 10126 Turin, Italy
*
Author to whom correspondence should be addressed.
Algorithms 2019, 12(10), 207; https://doi.org/10.3390/a12100207
Received: 15 July 2019 / Revised: 13 September 2019 / Accepted: 23 September 2019 / Published: 1 October 2019
Political parties recently learned that they must use social media campaigns along with advertising on traditional media to defeat their opponents. Before the campaign starts, it is important for a political party to establish and ensure its media presence, for example by enlarging their number of connections in the social network in order to assure a larger portion of users. Indeed, adding new connections between users increases the capabilities of a social network of spreading information, which in turn can increase the retention rate and the number of new voters. In this work, we address the problem of selecting a fixed-size set of new connections to be added to a subset of voters that, with their influence, will change the opinion of the network’s users about a target candidate, maximizing its chances to win the election. We provide a constant factor approximation algorithm for this problem and we experimentally show that, with few new links and small computational time, our algorithm is able to maximize the chances to make the target candidate win the elections. View Full-Text
Keywords: computational social choice; election control; influence maximization; social networks; graph augmentation; approximation algorithms computational social choice; election control; influence maximization; social networks; graph augmentation; approximation algorithms
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Corò, F.; D’Angelo, G.; Velaj, Y. Recommending Links to Control Elections via Social Influence. Algorithms 2019, 12, 207.

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