1. A method for detecting peer pressure in social media, comprising: receiving social media data from one or more social media platforms; analyzing the social media data to identify peer pressure behavior among social media users; generating a peer pressure score for each social media user based on the identified peer pressure behavior; and providing an output indicating the peer pressure score for each social media user.

2. The method of claim 1, wherein the social media data includes text, images, audio, or video content.

3. The method of claim 1, wherein the peer pressure behavior includes likes, comments, shares, or other forms of engagement with social media content.

4. The method of claim 1, wherein the peer pressure score is based on the frequency, intensity, or duration of the identified peer pressure behavior.

5. The method of claim 1, further comprising comparing the peer pressure score of a social media user to a peer pressure threshold to determine if the user is experiencing significant peer pressure.

6. The method of claim 1, further comprising providing recommendations or interventions to a social media user based on their peer pressure score.

7. A system for detecting peer pressure in social media, comprising: one or more processors configured to receive and analyze social media data from one or more social media platforms; a peer pressure detection module configured to identify peer pressure behavior among social media users based on the analyzed social media data; a peer pressure scoring module configured to generate a peer pressure score for each social media user based on the identified peer pressure behavior; and an output module configured to provide an output indicating the peer pressure score for each social media user.

8. The system of claim 7, further comprising a user interface module configured to display the peer pressure scores for one or more social media users.

9. The system of claim 7, further comprising a database module configured to store social media data and peer pressure scores for one or more social media users. PEER PRESSURE DETECTION THROUGH SOCIAL MEDIA Abstract The existing disclosure may allow for the deployment of a chatbot system with the intention of assisting a user in reducing their feelings of social anxiety. A system like this one may include an AI engine that is pre-programmed to take in information from the user and analyse it. In certain embodiments, there is additionally a user interface that may be incorporated. This user interface has the capability of collecting input from users and showing output that is developed in a responsive manner by an artificial intelligence engine. In certain implementations, there is also a social anxiety reduction module that is designed to provide responsive output depending on the analysis of user input performed by an AI engine. This kind of module may be included. Positive affirmations, exercises in mindfulness, exposure treatment, and cognitive-behavioral therapy are some examples of what could be included in the response output. , Claims:Claims :

1. A method for detecting peer pressure in social media, comprising: receiving social media data from one or more social media platforms; analyzing the social media data to identify peer pressure behavior among social media users; generating a peer pressure score for each social media user based on the identified peer pressure behavior; and providing an output indicating the peer pressure score for each social media user.

2. The method of claim 1, wherein the social media data includes text, images, audio, or video content.

3. The method of claim 1, wherein the peer pressure behavior includes likes, comments, shares, or other forms of engagement with social media content.

4. The method of claim 1, wherein the peer pressure score is based on the frequency, intensity, or duration of the identified peer pressure behavior.

5. The method of claim 1, further comprising comparing the peer pressure score of a social media user to a peer pressure threshold to determine if the user is experiencing significant peer pressure.

6. The method of claim 1, further comprising providing recommendations or interventions to a social media user based on their peer pressure score.

7. A system for detecting peer pressure in social media, comprising: one or more processors configured to receive and analyze social media data from one or more social media platforms; a peer pressure detection module configured to identify peer pressure behavior among social media users based on the analyzed social media data; a peer pressure scoring module configured to generate a peer pressure score for each social media user based on the identified peer pressure behavior; and an output module configured to provide an output indicating the peer pressure score for each social media user.

8. The system of claim 7, further comprising a user interface module configured to display the peer pressure scores for one or more social media users.

9. The system of claim 7, further comprising a database module configured to store social media data and peer pressure scores for one or more social media users.

Description:PEER PRESSURE DETECTION THROUGH SOCIAL MEDIA
Field of the Invention

[0001] This invention relates to a system and method for detecting and analyzing peer pressure through social media data, more particularly, to the system and method to provide an artificial intelligence platform for improving socialization outcomes for individuals with autism.
Background
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Peer pressure is a pervasive issue that has been studied for many years, and it can be defined as the influence that individuals or groups have on each other to conform to certain behaviors, attitudes, or beliefs. Peer pressure can have both positive and negative effects, and it can occur in various contexts, such as school, work, and social media.
[0004] With the rise of social media, peer pressure has become even more complex and challenging to detect. Social media platforms allow individuals to interact with a large network of friends and acquaintances, and these interactions can influence their behavior and decisions. Moreover, social media platforms often incentivize users to conform to popular trends and follow certain social norms.
[0005] While there have been some efforts to study peer pressure on social media, most of these studies have focused on specific platforms or limited aspects of peer pressure. There is a need for a comprehensive system and method that can detect and analyze peer pressure across various social media platforms and provide personalized recommendations to users. Few of the prior arts are listed below.
[0006] US20200051189A1 (By: CONQUER YOUR ADDICTION) The present disclosure generally relates to systems and methods for developing, monitoring, and enforcing agreements, understandings, and/or contracts (e.g., legal, technical, and social agreements, understandings, and/or contracts, legal, common law, or “handshake-like” agreements, etc.), such as by using behaviors and/or actions (e.g., pre-identified behaviors, pre-emptive actions, etc.) determined via one or more different devices, sensors, sensor arrays, and/or communications networks (e.g., the Internet of Things (IOT), social networks, etc.).
[0007] EP3234731B1 (By: SOMATIX) Methods and systems are provided herein for analyzing, monitoring, and/or influencing a user's behavioral gesture in real-time. A gesture recognition method may be provided. The method may comprise: obtaining sensor data collected using at least one sensor located on a wearable device, wherein said wearable device is configured to be worn by a user; and analyzing the sensor data to determine a probability of the user performing a predefined gesture, wherein the probability is determined based in part on a magnitude of a motion vector in the sensor data, and without comparing the motion vector to one or more physical motion profiles.
[0008] US9202111B2 (By: FITBIT) Methods, apparatuses, and systems are provided for determining a level of user engagement with a fitness monitoring device and, when a level of engagement metric for the fitness monitoring device for a person meets certain criteria, encouraging user engagement with the fitness monitoring device.
[0009] Existing systems that attempt to address this issue often rely on self-reported data or simple statistical analysis. These approaches have limitations and may not provide accurate insights into peer pressure. Therefore, there is a need for a more sophisticated system that can use machine learning algorithms to analyze social media data and identify patterns of behavior that suggest peer pressure.
[00010] All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.
[00011] It also shall be noted that as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. This invention can be achieved by means of hardware including several different elements or by means of a suitably programmed computer. In the unit claims that list several means, several ones among these means can be specifically embodied in the same hardware item. The use of such words as first, second, third does not represent any order, which can be simply explained as names.
Summary
[00012] The following presents a simplified summary of various aspects of this disclosure in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements nor delineate the scope of such aspects. Its purpose is to present some concepts of this disclosure in a simplified form as a prelude to the more detailed description that is presented later.
[00013] The following paragraphs provide additional support for the claims of the subject application.
[00014]
[00015] This invention relates to a system and method for detecting and analyzing peer pressure through social media data., more particularly, to the system and method to provide an artificial intelligence platform for improving socialization outcomes for individuals with autism.
[00016] Embodiments of the present disclosure may include a method for detecting peer pressure in social media, wherein the method includes receiving social media data from one or more social media platforms. Embodiments may also include analyzing the social media data to identify peer pressure behavior among social media users. Embodiments may also include generating a peer pressure score for each social media user based on the identified peer pressure behavior. Embodiments may also include providing an output indicating the peer pressure score for each social media user.
[00017] In some embodiments, the social media data includes text, images, audio, or video content. In some embodiments, the peer pressure behavior includes likes, comments, shares, or other forms of engagement with social media content. In some embodiments, the peer pressure score may be based on the frequency, intensity, or duration of the identified peer pressure behavior.
[00018] In some embodiments, the method may include comparing the peer pressure score of a social media user to a peer pressure threshold to determine if the user may be experiencing significant peer pressure. In some embodiments, the method may include providing recommendations or interventions to a social media user based on their peer pressure score.
[00019] Embodiments of the present disclosure may also include a system for detecting peer pressure in social media, including one or more processors configured to receive and analyze social media data from one or more social media platforms. Embodiments may also include a peer pressure detection module configured to identify peer pressure behavior among social media users based on the analyzed social media data. Embodiments may also include a peer pressure scoring module configured to generate a peer pressure score for each social media user based on the identified peer pressure behavior. Embodiments may also include an output module configured to provide an output indicating the peer pressure score for each social media user.
[00020] In some embodiments, the system may include a user interface module configured to display the peer pressure scores for one or more social media users. In some embodiments, the system may include a database module configured to store social media data and peer pressure scores for one or more social media users.
Brief Description of the Drawings
[00021] The features and advantages of the present disclosure would be more clearly understood from the following description taken in conjunction with the accompanying drawings in which:
[00022] FIG. 1 is a flowchart illustrating a method for detecting peer pressure in social media, according to some embodiments of the present disclosure.
[00023] FIG. 2 is a block diagram illustrating a system for detecting peer pressure in social media, according to some embodiments of the present disclosure.
Detailed Description
[00024] In the following detailed description of the invention, reference is made to the accompanying drawings that form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the invention may be practiced. In the drawings, like numerals describe substantially similar components throughout the several views. These embodiments are described in sufficient detail to claim those skilled in the art to practice the invention. Other embodiments may be utilized and structural, logical, and electrical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims and equivalents thereof.
[00025] The use of the terms “a” and “an” and “the” and “at least one” and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The use of the term “at least one” followed by a list of one or more items (for example, “at least one of A and B”) is to be construed to mean one item selected from the listed items (A or B) or any combination of two or more of the listed items (A and B), unless otherwise indicated herein or clearly contradicted by context. The terms “comprising,” “having,” “including,” and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to,”) unless otherwise noted. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention..

[00026] This invention relates to a system and method for detecting and analyzing peer pressure through social media data., more particularly, to the system and method to provide an artificial intelligence platform for improving socialization outcomes for individuals with autism.
[00027] A flowchart depicting one embodiment of a technique for identifying instances of peer pressure in social media is shown in Figure 1. This method is in accordance with certain aspects of the current disclosure. Receiving social media data from one or more social media sites may be part of the technique in a number of different implementations, namely at step 110. At step 120, the technique may involve conducting an analysis of the data collected from social media in order to determine the extent to which social media users are influenced by their peers. At step 130, the technique can involve calculating a peer pressure score for each user of a social media platform based on the peer pressure behaviours that have been recognised. At the 140 mark, the system might involve delivering an output that indicates the level of peer pressure experienced by each social media user.
[00028] In some implementations, the data collected from social media may consist of text, photos, audio, or video information. In certain implementations, the conduct that constitutes peer pressure may take the shape of likes, comments, shares, or other types of interaction with information found on social media. The peer pressure score may, in certain implementations, be determined by the frequency, intensity, or length of the behaviours that are considered to be examples of peer pressure. Comparing the peer pressure score of a social media user to a threshold for determining whether or not the user may be subject to considerable peer pressure is one such step that may be included in some implementations of the approach. A social media user may be provided with suggestions or interventions as part of the approach in certain implementations of the method.
[00029] A system 200 is shown in block diagram form in FIG. 2, which provides a description of the system in accordance with various aspects of the current disclosure for detecting peer pressure in social media. The system 200 may, in some implementations, contain one or more processors 210 that are programmed to receive and analyse social media data from one or more social media platforms; a peer pressure detection module 220 that is programmed to identify peer pressure behaviour among social media users based on the analysed social media data; a peer pressure scoring module 230 that is programmed to generate a peer pressure score for each social media user based on the identified peer pressure behaviour; and a user interface module that is capable of displaying the peer pressure scores for one or more social media users may be included in some implementations of the system 200. A database module that is able to store social media data as well as peer pressure ratings for one or more social media users may be included in various implementations of the system 200.
[00030] This method and system aim to detect and quantify the peer pressure experienced by social media users, based on their interactions with social media content. The system comprises one or more processors that are configured to receive and analyze social media data from one or more social media platforms, such as Facebook, Twitter, Instagram, or Snapchat. The social media data may include text, images, audio, or video content, which is analyzed to identify peer pressure behavior among social media users.
[00031] The peer pressure behavior may include likes, comments, shares, or other forms of engagement with social media content that suggest conformity to group norms or pressure to conform. For example, if a user frequently likes or shares posts related to a certain trend or popular opinion, it may indicate that the user is experiencing peer pressure to conform to that trend or opinion. The system analyzes such behavior to identify patterns and trends in the user's social media activity that suggest peer pressure.
[00032] Based on the identified peer pressure behavior, the system generates a peer pressure score for each social media user, which reflects the extent and intensity of their peer pressure experience. The peer pressure score may be based on the frequency, intensity, or duration of the identified peer pressure behavior. For example, if a user frequently engages with social media content that promotes a certain body image or lifestyle, it may indicate that they are experiencing high levels of peer pressure related to that aspect.
[00033] The system also includes a peer pressure detection module that identifies and quantifies peer pressure behavior among social media users and a peer pressure scoring module that generates a peer pressure score for each user based on the identified peer pressure behavior. Additionally, an output module is included that provides an output indicating the peer pressure score for each social media user.
[00034] The system further includes a user interface module that displays the peer pressure scores for one or more social media users. The user interface may be a graphical interface or a command-line interface, which enables users to view and interact with the peer pressure scores of other social media users. Additionally, the system includes a database module that stores social media data and peer pressure scores for one or more social media users, which enables the system to maintain a historical record of users' peer pressure experiences.
[00035] Finally, the system may include a feature to compare the peer pressure score of a social media user to a peer pressure threshold to determine if the user is experiencing significant peer pressure. If a user's peer pressure score exceeds the threshold, the system may provide recommendations or interventions to help the user cope with the pressure, such as suggesting resources for mental health or connecting them with support groups.
[00036] A method for identifying peer pressure in social media may be included in certain embodiments of the present disclosure. This method may include collecting data from one or more social media platforms in order to gather social media information. Analyzing the data from social media to determine whether or not its users are susceptible to being influenced by their peers is another possible embodiment. In certain embodiments, there is also the possibility of calculating a peer pressure score for each user of a social media platform, based on the behaviours that are classified as constituting peer pressure. The provision of an output that indicates the degree to which each social media user is influenced by their peers is another possible embodiment.
[00037] Text, photos, audio, and video information may be included as part of the social media data in some implementations. Likes, comments, shares, and other kinds of involvement with social media material may be examples of peer pressure behaviours in some implementations of the invention. The peer pressure score may, in certain implementations, be determined by the frequency, intensity, or length of the behaviours that are considered to be examples of peer pressure.
[00038] Comparing the peer pressure score of a social media user to a threshold for determining whether or not the user may be subject to considerable peer pressure is one such step that may be included in some implementations of the approach. A social media user may be provided with suggestions or interventions as part of the approach in certain implementations of the method. This is done on the basis of the user's peer pressure score.
[00039] The present disclosure may also include embodiments of a system for detecting peer pressure in social media, which may include one or more processors configured to receive and analyse social media data from one or more social media platforms. A peer pressure detection module that is designed to recognise peer pressure behaviour among social media users may also be included in embodiments. This behaviour can be determined based on the analysed social media data. A peer pressure scoring module that is designed to create a peer pressure score for each social media user based on the recognised peer pressure behaviour may also be included in embodiments. In certain embodiments, there is also a possibility of including an output module that is designed to produce an output reflecting the level of peer pressure experienced by each social media user.
[00040] A user interface module that is capable of displaying the peer pressure scores for one or more social media users may be included in the system according to certain implementations of this component. A database module that is able to hold social media data as well as peer pressure ratings for one or more social media users may be included in the system according to various implementations of the system.
[00041] Example embodiments herein have been described above with reference to block diagrams and flowchart illustrations of methods and apparatuses. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by various means including hardware, software, firmware, and a combination thereof. For example, in one embodiment, each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations can be implemented by computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.
[00042] Throughout the present disclosure, the term ‘Artificial intelligence (AI)’ as used herein relates to any mechanism or computationally intelligent system that combines knowledge, techniques, and methodologies for controlling a bot or other element within a computing environment. Furthermore, the artificial intelligence (AI) is configured to apply knowledge and that can adapt it-self and learn to do better in changing environments. Additionally, employing any computationally intelligent technique, the artificial intelligence (AI) is operable to adapt to unknown or changing environment for better performance. The artificial intelligence (AI) includes fuzzy logic engines, decision-making engines, preset targeting accuracy levels, and/or programmatically intelligent software.
[00043] Throughot the present disclosure, the term ‘processing means’ or ‘microprocessor’ or ‘processor’ or ‘processors’ includes, but is not limited to, a general purpose processor (such as, for example, a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a microprocessor implementing other types of instruction sets, or a microprocessor implementing a combination of types of instruction sets) or a specialized processor (such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), or a network processor).
[00044] The term “non-transitory storage device” or “storage” or “memory,” as used herein relates to a random access memory, read only memory and variants thereof, in which a computer can store data or software for any duration. Operations in accordance with a variety of aspects of the disclosure is described above would not have to be performed in the precise order described. Rather, various steps can be handled in reverse order or simultaneously or not at all.
[00045] While several implementations have been described and illustrated herein, a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein may be utilized, and each of such variations and/or modifications is deemed to be within the scope of the implementations described herein. More generally, all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific implementations described herein. It is, therefore, to be understood that the foregoing implementations are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, implementations may be practiced otherwise than as specifically described and claimed. Implementations of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the scope of the present disclosure.
 

Claims
I/We Claim:
1. A method for detecting peer pressure in social media, comprising:
receiving social media data from one or more social media platforms;
analyzing the social media data to identify peer pressure behavior among social media users;
generating a peer pressure score for each social media user based on the identified peer pressure behavior; and
providing an output indicating the peer pressure score for each social media user.

2. The method of claim 1, wherein the social media data includes text, images, audio, or video content.

3. The method of claim 1, wherein the peer pressure behavior includes likes, comments, shares, or other forms of engagement with social media content.

4. The method of claim 1, wherein the peer pressure score is based on the frequency, intensity, or duration of the identified peer pressure behavior.

5. The method of claim 1, further comprising comparing the peer pressure score of a social media user to a peer pressure threshold to determine if the user is experiencing significant peer pressure.

6. The method of claim 1, further comprising providing recommendations or interventions to a social media user based on their peer pressure score.

7. A system for detecting peer pressure in social media, comprising:
one or more processors configured to receive and analyze social media data from one or more social media platforms;
a peer pressure detection module configured to identify peer pressure behavior among social media users based on the analyzed social media data;
a peer pressure scoring module configured to generate a peer pressure score for each social media user based on the identified peer pressure behavior; and
an output module configured to provide an output indicating the peer pressure score for each social media user.

8. The system of claim 7, further comprising a user interface module configured to display the peer pressure scores for one or more social media users.

9. The system of claim 7, further comprising a database module configured to store social media data and peer pressure scores for one or more social media users.

PEER PRESSURE DETECTION THROUGH SOCIAL MEDIA
Abstract
The existing disclosure may allow for the deployment of a chatbot system with the intention of assisting a user in reducing their feelings of social anxiety. A system like this one may include an AI engine that is pre-programmed to take in information from the user and analyse it. In certain embodiments, there is additionally a user interface that may be incorporated. This user interface has the capability of collecting input from users and showing output that is developed in a responsive manner by an artificial intelligence engine. In certain implementations, there is also a social anxiety reduction module that is designed to provide responsive output depending on the analysis of user input performed by an AI engine. This kind of module may be included. Positive affirmations, exercises in mindfulness, exposure treatment, and cognitive-behavioral therapy are some examples of what could be included in the response output. , Claims:Claims
I/We Claim:
1. A method for detecting peer pressure in social media, comprising:
receiving social media data from one or more social media platforms;
analyzing the social media data to identify peer pressure behavior among social media users;
generating a peer pressure score for each social media user based on the identified peer pressure behavior; and
providing an output indicating the peer pressure score for each social media user.

2. The method of claim 1, wherein the social media data includes text, images, audio, or video content.

3. The method of claim 1, wherein the peer pressure behavior includes likes, comments, shares, or other forms of engagement with social media content.

4. The method of claim 1, wherein the peer pressure score is based on the frequency, intensity, or duration of the identified peer pressure behavior.

5. The method of claim 1, further comprising comparing the peer pressure score of a social media user to a peer pressure threshold to determine if the user is experiencing significant peer pressure.

6. The method of claim 1, further comprising providing recommendations or interventions to a social media user based on their peer pressure score.

7. A system for detecting peer pressure in social media, comprising:
one or more processors configured to receive and analyze social media data from one or more social media platforms;
a peer pressure detection module configured to identify peer pressure behavior among social media users based on the analyzed social media data;
a peer pressure scoring module configured to generate a peer pressure score for each social media user based on the identified peer pressure behavior; and
an output module configured to provide an output indicating the peer pressure score for each social media user.

8. The system of claim 7, further comprising a user interface module configured to display the peer pressure scores for one or more social media users.

9. The system of claim 7, further comprising a database module configured to store social media data and peer pressure scores for one or more social media users.