On bundle configuration for viral marketing in social networks

Yang, De-Nian; Lee, Wang-Chien; Chia, Nai-Hui; Ye, Mao; Hung, Hui-Ju

doi:10.1145/2396761.2398608

Cited by 11 publications

(9 citation statements)

References 8 publications

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“…It is worth noting that the illustrating example in the paper is symmetric for simplicity. As demonstrated in the previous works in Psychology and social networks [23], [24] that jointly consider the social and interest domains, the willingness of a group is represented as the sum of the topic interest of nodes and social tightness between them 7 . Notice that the network with η as 0 or τ as 0 is a special case of WASO.…”

Section: Problem Definitionmentioning

confidence: 99%

“…Thus, the above studies provide a sound foundation to quantify the user interest and social tightness scores in social networks. Moreover, Yang [23] and Lee [24] sum up the two factors as willingness for marketing and recommendation. Nevertheless, the above factors crucial in social networks have not been leveraged for automatic activity planning explored in this paper.…”

Section: Related Workmentioning

confidence: 99%

“…It is desirable to choose more attendees who like and enjoy the activity and to invite more friends with the shared interest in the In fact, Psychology [8], [14] and recent study in social networks [23], [24] have modeled the willingness to attend an activity or a social event as the sum of the interest of each attendee on the activity and the social tightness between friends that are possible to join it. It is envisaged that the selected attendees are more inclined to join the activity if the willingness of the group increases.…”

Section: Introductionmentioning

confidence: 99%

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A Comprehensive Study on Willingness Maximization for Social Activity Planning with Quality Guarantee

Shuai

Yang

et al. 2016

IEEE Trans. Knowl. Data Eng.

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Studies show that a person is willing to join a social group activity if the activity is interesting, and if some close friends also join the activity as companions. The literature has demonstrated that the interests of a person and the social tightness among friends can be effectively derived and mined from social networking websites. However, even with the above two kinds of information widely available, social group activities still need to be coordinated manually, and the process is tedious and time-consuming for users, especially for a large social group activity, due to complications of social connectivity and the diversity of possible interests among friends. To address the above important need, this paper proposes to automatically select and recommend potential attendees of a social group activity, which could be very useful for social networking websites as a valueadded service. We first formulate a new problem, named Willingness mAximization for Social grOup (WASO). This paper points out that the solution obtained by a greedy algorithm is likely to be trapped in a local optimal solution. Thus, we design a new randomized algorithm to effectively and efficiently solve the problem. Given the available computational budgets, the proposed algorithm is able to optimally allocate the resources and find a solution with an approximation ratio. We implement the proposed algorithm in Facebook, and the user study demonstrates that social groups obtained by the proposed algorithm significantly outperform the solutions manually configured by users.Index Terms-Social network, query processing, optimization ✦ 2. The privacy of a person in automatic activity planning can follow the current privacy setting policy in social networking websites when the person subscribes the service. The details of privacy setting are beyond the scope of this paper.

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Section: Problem Definitionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive Study on Willingness Maximization for Social Activity Planning with Quality Guarantee

Shuai

Yang

et al. 2016

IEEE Trans. Knowl. Data Eng.

Self Cite

View full text Add to dashboard Cite

show abstract

“…It is worth noting that the illustrating example in the paper is symmetric for simplicity. As demonstrated in the previous works in Psychology and social networks [22,23] that jointly consider the social and interest domains, the willingness of a group is represented as the sum of the topic interest of nodes and social tightness between them 7 . Notice that the network with η as 0 or τ as 0 is a special case of WASO.…”

Section: Preliminary 21 Problem Definitionmentioning

confidence: 99%

“…It is desirable to choose more attendees who like and enjoy the activity and to invite more friends with the shared interest in the activity as companions. In fact, Psychology [8,14] and recent study in social networks [22,23] have modeled the willingness to attend an activity or a social event as the sum of the interest of each attendee on the activity and the social tightness between friends that are possible to join it. It is envisaged that the selected attendees are more inclined to join the activity if the willingness of the group increases.…”

Section: Introductionmentioning

confidence: 99%

Willingness optimization for social group activity

Shuai

Yang

et al. 2013

Proc. VLDB Endow.

Self Cite

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Studies show that a person is willing to join a social group activity if the activity is interesting, and if some close friends also join the activity as companions. The literature has demonstrated that the interests of a person and the social tightness among friends can be effectively derived and mined from social networking websites. However, even with the above two kinds of information widely available, social group activities still need to be coordinated manually, and the process is tedious and time-consuming for users, especially for a large social group activity, due to complications of social connectivity and the diversity of possible interests among friends. To address the above important need, this paper proposes to automatically select and recommend potential attendees of a social group activity, which could be very useful for social networking websites as a value-added service. We first formulate a new problem, named Willingness mAximization for Social grOup (WASO). This paper points out that the solution obtained by a greedy algorithm is likely to be trapped in a local optimal solution. Thus, we design a new randomized algorithm to effectively and efficiently solve the problem. Given the available computational budgets, the proposed algorithm is able to optimally allocate the resources and find a solution with an approximation ratio. We implement the proposed algorithm in Facebook, and the user study demonstrates that social groups obtained by the proposed algorithm significantly outperform the solutions manually configured by users.

show abstract