METHOD AND SYSTEM FOR QUANTIFYING AN INDIVIDUAL'S SOCIAL FAME (SF) IN SOCIAL MEDIA
The present invention provides a method for quantifying an individual's Social Fame (SF) in social media and a system thereof. The method includes the following steps: collecting social media data of the individual from various social media platforms; assigning a weight parameter to each social media platform from which the social media data is collected; identifying whether a post or a response contained in the collected social media data is positive or negative by sentiment analysis performed by a generative AI model; and calculating the individual's SF score based on the collected social media data, the weight parameter of each social media platform, and the sentiment analysis results.
1 . A method for quantifying an individual's Social Fame (SF) in social media, comprising the steps of:
collecting social media data of the individual from various social media platforms;
assigning a weight parameter to each social media platform from which the social media data is collected;
identifying whether a post or a response contained in the collected social media data is positive or negative by sentiment analysis performed by a generative AI model; and
calculating the individual's SF score based on the collected social media data, the weight parameter of each social media platform, and sentiment analysis results.
2 . The method according to claim 1 , wherein the collected social media data comprises a number of positive posts and a number of negative posts made by the individual on each social media platform during a specific period of time.
3 . The method according to claim 1 , wherein the collected social media data comprises a number of positive responses and a number of negative responses received by the individual on each social media platform during a specific period of time by a selected group of people.
4 . The method according to claim 1 , wherein the collected social media data comprises a number of positive responses made by the individual toward another person during a specific period of time.
5 . The method according to claim 1 , wherein the individual's SF score decreases when the individual gives a positive response to another person.
6 . The method according to claim 1 , wherein the SF score is calculated by multiplying the weight parameter assigned to each social media platform by the disparity between the quantity of positive and negative posts/responses collected during a specific time period, as determined by the sentiment analysis results.
7 . The method according to claim 1 , wherein the SF score is dynamically updated according to the social media data which is collected in real-time.
8 . The method according to claim 1 , wherein the SF score is dynamically adjusted and updated to a SF database and is displayed through an application programming interface (API) Gateway.
9 . The method according to claim 1 , wherein the weight parameter assigned to each social media platform is based on a credibility score and a detrimental score thereof.
10 . The method according to claim 1 , further comprising a step of:
evaluating an activity level of the individual on each social media platform.
11 . A system for quantifying an individual's Social Fame (SF) in social media, comprising:
a user database, for storing an individual's profile including current and historical SF scores;
a social media data collector, network-connected to the user database and various social media platforms, for collecting social media data of the individual from various social media platforms;
an AI integration engine, network-connected to the social media data collector, for identifying whether a post or a response contained in the collected social media data is positive or negative by sentiment analysis performed by a generative AI model; and
a calculation engine, network-connected to the AI integration engine, for assigning a weight parameter to each social media platform from which the social media data is collected, and for calculating the individual's SF score based on the collected social media data, the weight parameter of each social media platform, and the sentiment analysis results.
12 . The system according to claim 11 , wherein the collected social media data comprises a number of positive posts and a number of negative posts made by the individual on each social media platform during a specific period of time.
13 . The system according to claim 11 , wherein the collected social media data comprises a number of positive responses and a number of negative responses received by the individual on each social media platform during a specific period of time by a selected group of people.
14 . The system according to claim 11 , wherein the collected social media data comprises a number of positive responses made by the individual toward another person during a specific period of time.
15 . The system according to claim 11 , wherein the individual's SF score decreases when the individual gives a positive response to another person.
16 . The system according to claim 11 , wherein the SF score is calculated by multiplying the weight parameter assigned to each social media platform by the disparity between the quantity of positive and negative posts/responses collected during a specific time period, as determined by the sentiment analysis results.
17 . The system according to claim 11 , wherein the SF score is dynamically updated according to the social media data which is collected in real-time.
18 . The system according to claim 11 , wherein the SF score is dynamically adjusted and updated to the user database and is displayed through an application programming interface (API) Gateway.
19 . The system according to claim 11 , wherein the weight parameter assigned to each social media platform by the calculation engine is based on a credibility score and a detrimental score thereof.
20 . The system according to claim 11 , wherein the calculation engine further evaluates an activity level of the individual on each social media platform.