US 9,852,478 B2Granted

Identifying influencers in computer networks

AssigneeInternational Business Machines Corporation

InventorsJonathan Herzig, Yosi Mass, Haggai Roitman

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Abstract

Identifying influencers in a computer network by adjusting influence weights of corresponding participants of a computer network, where the influence weights relate to a topic, where each of the influence weights is adjusted in accordance with a predefined adjustment function, and where the predefined adjustment function uses a) the influence weight of any of the participants that disseminated content via the computer network, where the content relates to the participant whose influence weight is being adjusted, b) a participant topic similarity value of any of the participants that disseminated the content, where the participant topic similarity value relates to the topic, and c) a relationship topic similarity value of any relationship between the participants that disseminated the content and the participant whose influence weight is being adjusted, where the relationship topic similarity value relates to the topic, and then ranking the participants by their influence weights.

Claims17

Dependent claims

A method for identifying influencers in a computer network, the method comprising:

adjusting a plurality of influence weights of a corresponding plurality of participants of the computer network, wherein the influence weights relate to a topic, wherein each of the influence weights is adjusted in accordance with a predefined adjustment function, and wherein the predefined adjustment function is:
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where:
d is a user-defined factor which determines whether more importance is assigned to a participant topic similarity value of participant u, or to a plurality of relationship topic similarity values of relationships with other participants who disseminated content relating to participant u;
RDT(u) is a sum of the influence weights of a portion of the plurality of participants about whom there is no content relating to said portion of the plurality of participants in a collection of content;
αT(u) is the participant topic similarity value of the participant u;
In(u) is a set of participants who have a relationship with the participant u by having disseminated the content relating to the participant u;
βT(evu) is a relationship topic similarity value of a relationship with another participant who disseminated the content relating to the participant u;
and
RT(v) is an influence weight for a user v who cited the participant u;
ranking the plurality of participants by their influence weights;
and
transmitting the content via a portion of the plurality of participants with a rank above a threshold.

72 more elements

A system for identifying influencers in a computer network, the system comprising:

a processor to:
adjust a plurality of influence weights of a corresponding plurality of participants of the computer network, wherein the influence weights relate to a topic, wherein each of the influence weights is adjusted in accordance with a predefined adjustment function, and wherein the predefined adjustment function is:
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where:
d is a user-defined factor which determines whether more importance is assigned to a participant topic similarity value of participant u, or to a plurality of relationship topic similarity values of relationships with other participants who disseminated content relating to participant u;
RDT(u) is a sum of the influence weights of a portion of the plurality of participants about whom there is no content relating to said portion of the plurality of participants in a collection of content;
αT(u) is the participant topic similarity value of the participant u;
In(u) is a set of participants who have a relationship with the participant u by having disseminated the content relating to the participant u;
βT(evu) is a relationship topic similarity value of a relationship with another participant who disseminated the content relating to the participant u;
and
RT(v) is an influence weight for a user v who cited the participant u;
rank the plurality of participants by their influence weights;
and
transmit the content via a portion of the plurality of participants with a rank above a threshold.

73 more elements

A computer program product for identifying influencers in a computer network, the computer program product comprising:

a non-transitory, computer-readable storage medium;
and
computer-readable program code embodied in the storage medium, wherein the computer-readable program code is configured to
adjust a plurality of influence weights of a corresponding plurality of participants of the computer network, wherein the influence weights relate to a topic, wherein each of the influence weights is adjusted in accordance with a predefined adjustment function, and wherein the predefined adjustment function is:
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where:
d is a user-defined factor which determines whether more importance is assigned to a participant topic similarity value of participant u, or to a plurality of relationship topic similarity values of relationships with other participants who disseminated content relating to participant u;
RDT(u) is a sum of the influence weights of a portion of the plurality of participants about whom there is no content relating to said portion of the plurality of participants in a collection of content;
αT(u) is the participant topic similarity value of the participant u;
In(u) is a set of participants who have a relationship with the participant u by having disseminated the content relating to the participant u;
βT(evu) is a relationship topic similarity value of a relationship with another participant who disseminated the content relating to the participant u;
and
RT(v) is an influence weight for a user v who cited the participant u;
and
wherein the computer-readable program code is configured to rank the plurality of participants by their influence weights and transmit the content via a portion of the plurality of participants with a rank above a threshold.

74 more elements

Dependencies are inferred from the claim text.

Facts

Application: 14/463,681Filed 20 Aug 2014
Published: US 2016/0055253 A125 Feb 2016
Granted: 26 Dec 2017
Term ends: Not estimatedThe source records don’t support an estimate.

Classification4 codes

G06F 16/9535
Querying, e.g. by the use of web search engines: search customisation based on user profiles and personalisation
G06Q 10/46
Business processes related to social networking or social networking services: determination of level of influence of users within social…
G06F
Computing and data processing
G06Q
Information and communication technology [ict] specially adapted for administrative, commercial, financial, managerial