1. A system for narcissist personality detection based on written text processing, comprising: a text analysis module for parsing written text data, a machine learning module for training a model to detect narcissistic language patterns; and a detection module for identifying narcissistic language in the analysed text data.

2. The system of claim 1, wherein the text analysis module uses natural language processing (NLP) techniques to analyse written text data and extract linguistic features such as word usage, sentence structure, and discourse coherence.

3. The system of claim 1, wherein the machine learning module uses supervised learning techniques to train a model to identify linguistic patterns associated with narcissistic personality traits.

4. The system of claim 1, wherein the detection module applies the trained model to the analysed text data to identify instances of narcissistic language.

5. The system of claim 1, wherein the text analysis module further includes a sentiment analysis component to identify the emotional tone of the written text data, and a visualization component to display the results of the analysis.

6. A method for narcissist personality detection based on written text processing, comprising: parsing written text data using natural language processing techniques; training a machine learning model to identify linguistic patterns associated with narcissistic personality traits; and identifying instances of narcissistic language in the analysed text data using the trained model.

7. The method of claim 6, further comprising analysing the emotional tone of the written text data using a sentiment analysis component.

8. The method of claim 7, wherein the machine learning model is trained using a labelled dataset of written text data that includes instances of narcissistic language.

9. The method of claim 7, wherein the identified instances of narcissistic language are used to provide personalized feedback to individuals on their communication style.

10. The method of claim 7, wherein the identified instances of narcissistic language are used to identify potential risks associated with narcissistic behaviour in the workplace or in personal relationships. NARCISSIST PERSONALITY DETECTION BASED ON LANGUAGE PARSING Abstract A system for narcissist personality detection based on written text processing may be included in some embodiments of the present disclosure. This system may include a text analysis module for parsing written text data, a machine learning module for training a model to detect narcissistic language patterns, and a detection module for identifying narcissistic language in the analysed text data. Fig. 1 , Claims:Claims :

1. A system for narcissist personality detection based on written text processing, comprising: a text analysis module for parsing written text data, a machine learning module for training a model to detect narcissistic language patterns; and a detection module for identifying narcissistic language in the analysed text data.

2. The system of claim 1, wherein the text analysis module uses natural language processing (NLP) techniques to analyse written text data and extract linguistic features such as word usage, sentence structure, and discourse coherence.

3. The system of claim 1, wherein the machine learning module uses supervised learning techniques to train a model to identify linguistic patterns associated with narcissistic personality traits.

4. The system of claim 1, wherein the detection module applies the trained model to the analysed text data to identify instances of narcissistic language.

5. The system of claim 1, wherein the text analysis module further includes a sentiment analysis component to identify the emotional tone of the written text data, and a visualization component to display the results of the analysis.

6. A method for narcissist personality detection based on written text processing, comprising: parsing written text data using natural language processing techniques; training a machine learning model to identify linguistic patterns associated with narcissistic personality traits; and identifying instances of narcissistic language in the analysed text data using the trained model.

7. The method of claim 6, further comprising analysing the emotional tone of the written text data using a sentiment analysis component.

8. The method of claim 7, wherein the machine learning model is trained using a labelled dataset of written text data that includes instances of narcissistic language.

9. The method of claim 7, wherein the identified instances of narcissistic language are used to provide personalized feedback to individuals on their communication style.

10. The method of claim 7, wherein the identified instances of narcissistic language are used to identify potential risks associated with narcissistic behaviour in the workplace or in personal relationships.

Description:NARCISSIST PERSONALITY DETECTION BASED ON LANGUAGE PARSING
Field of the Invention
[0001] The present invention relates to advance language processing for psychological evaluation of user. More specifically to system and method for language parsing based narcissist personality detection.
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] Narcissism is a personality trait characterized by an inflated sense of self-importance, a need for admiration, and a lack of empathy for others. Individuals with high levels of narcissism may exhibit problematic behaviours, such as arrogance, entitlement, and a disregard for the feelings and needs of others. Thus, Narcissistic individuals may have difficulty forming and maintaining relationships, and their behaviour can have a negative impact on those around them. Detecting narcissism in individuals can be a challenging task, especially in situations where face-to-face interaction is not possible.
[0004] Detecting narcissism in individuals is an important task in psychology, as it can aid in diagnosis, treatment, and prevention of negative outcomes associated with this personality trait. Various patent disclosure discloses methods for assessing narcissism.
[0005] US20160328992A1 (By: DHARMA LIFE SCIENCES) - A system is provided for enabling a user to overcome low self-esteem and narcissism. The system is configured to receive input indicating the desire to overcome low self-esteem and narcissism. The system is configured to enable the user to engage in a first, a second, a third and a fourth activity in a virtual environment, directed to rewire a first, second, third and a fourth defective wiring respectively. Symptoms of the first, second, third and the fourth defective wirings is at least one of low self-esteem and narcissism. Automated instructions are provided to the user to engage in activities performed in a real world environment directed to rewire the first, second, third and fourth defective wiring.
[0006] CA2269253A1 (By: HARDER RODNEY) - A method and apparatus for securing consumer attention. A dynamic live image is provided of a prospective consumer. A vantage point is provided from which the prospective consumer views the live image. Advertisements are positioned around the periphery of the live image, such that in order to view the live image the consumer must view the advertisements. The method and apparatus are based upon narcissistic human behaviour.
[0007] However, traditional techniques such as self-report measures and clinical interviews, have limitations, such as social desirability bias and subjectivity. Therefore, there is a need for objective, reliable, and efficient methods for detecting narcissism.

Summary
[0008] 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.
[0009] The following paragraphs provide additional support for the claims of the subject application.
[00010] The present invention relates to advance language processing for psychological evaluation of user. More specifically to system and method for language parsing based narcissist personality detection.
[00011] Embodiments of the present disclosure may include a system for narcissist personality detection based on written text processing, wherein the system includes a text analysis module for parsing written text data, a machine learning module for training a model to detect narcissistic language patterns, and a detection module for identifying narcissistic language in the analysed text data. In some embodiments, the text analysis module uses natural language processing (NLP) techniques to analyse written text data and extract linguistic features such as word usage, sentence structure, and discourse coherence.
[00012] In some embodiments, the machine learning module uses supervised learning techniques to train a model to identify linguistic patterns associated with narcissistic personality traits. In some embodiments, the detection module applies the trained model to the analysed text data to identify instances of narcissistic language. In some embodiments, the text analysis module further includes a sentiment analysis component to identify the emotional tone of the written text data, and a visualization component to display the results of the analysis.
[00013] Embodiments of the present disclosure may also include a method for narcissist personality detection based on written text processing, including parsing written text data using natural language processing techniques. Embodiments may also include training a machine learning model to identify linguistic patterns associated with narcissistic personality traits. Embodiments may also include identifying instances of narcissistic language in the analysed text data using the trained model.
[00014] In some embodiments, the method may include analysing the emotional tone of the written text data using a sentiment analysis component. In some embodiments, the machine learning model may be trained using a labelled dataset of written text data that includes instances of narcissistic language. In some embodiments, the identified instances of narcissistic language may be used to provide personalized feedback to individuals on their communication style. In some embodiments, the identified instances of narcissistic language may be used to identify potential risks associated with narcissistic behaviour in the workplace or in personal relationships.
Brief Description of the Drawings
[00015] 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:
[00016] FIG. 1 is a block diagram illustrating a system for narcissist personality detection based on written text processing, according to some embodiments of the present disclosure.
[00017] FIG. 2 is a flowchart illustrating a method for narcissist personality detection based on written text processing, according to some embodiments of the present disclosure.
Detailed Description
[00018] 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.
[00019] 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.
[00020] The present invention relates to advance language processing for psychological evaluation of user. More specifically to system and method for language parsing based narcissist personality detection.
[00021] A system 100 is broken down into its component parts and diagrammatically shown in FIG. 1 for narcissist personality detection based on written text processing, in accordance with various implementations of the present disclosure. The system 100 may also include a text analysis module 110 for the purpose of parsing written text data, a machine learning module for the purpose of training a model to detect narcissistic language patterns, and a detection module for the purpose of identifying narcissistic language in the analysed text data. Each of these modules may be included in some embodiments of the system. The text analysis module 110 may, in certain implementations, use natural language processing (NLP) methods in order to analyse written text data and extract linguistic properties such as word usage, sentence structure, and discourse coherence.
[00022] In some implementations, the machine learning module may use supervised learning strategies in order to educate a model in order to recognise language patterns that are related with narcissistic personality characteristics. In some implementations, the detection module will identify instances of narcissistic language by applying the trained model to the analysed text data(this is done so as to improve accuracy). The text analysis module 110 may, in certain implementations, further comprise a sentiment analysis component for the purpose of determining the emotional tenor (interchangeably referred as emotional tone) of the written text data as well as a visualisation component for the purpose of displaying the findings of the analysis.
[00023] A method is shown in flowchart form in FIG. 2, which discloses the technique in accordance with certain implementations of the current disclosure. In certain implementations of the method, step 210 may include applying natural language processing strategies to written text data in order to perform data parsing. In step 220, the technique may involve training a machine learning model to recognise language patterns that are related with narcissistic personality characteristics. Using the trained model, step 230 of the technique may include locating occurrences of narcissistic language within the analysed text data. Using a sentiment analysis component to do an analysis of the emotional tenor of the written text data may be included in some implementations of the approach.
[00024] The machine learning model may be trained in certain implementations by employing a tagged dataset of written text data that contains examples of narcissistic language. The instances of narcissistic language that have been found may, in certain implementations, be utilised to provide people individualised feedback on how they should improve their communication skills. The examples of narcissistic language that have been detected may, in certain implementations, be utilised to determine the possible dangers that may be linked with narcissistic behaviour in the workplace or in personal relationships.
[00025] A system for narcissist personality detection based on written text processing may be included in some embodiments of the present disclosure. This system may include a text analysis module for parsing written text data, a machine learning module for training a model to detect narcissistic language patterns, and a detection module for identifying narcissistic language in the analysed text data. The text analysis module, in certain implementations, applies natural language processing (NLP) methods in order to analyse written text data and extract linguistic aspects such as word use, sentence structure, and discourse coherence. This may be done in a number of different ways.
[00026] In certain implementations, the machine learning module will train a model to recognise language patterns that are related with narcissistic personality characteristics via the use of supervised learning methods. In certain implementations, the detection module identifies instances of narcissistic language by applying the trained model to the analysed text data (this helps the module avoid false positives). The text analysis module, in certain implementations, also contains a sentiment analysis component to determine the emotional tenor of the written text data and a visualisation component to present the findings of the analysis. Both of these components are used to exhibit the findings of the analysis.
[00027] A method for detecting narcissist personalities based on the processing of written text may also be included in certain embodiments of the present disclosure. This method may use methods for parsing written text data utilising natural language processing techniques. In certain embodiments, the process of identifying language patterns associated with narcissistic personality characteristics may also include training a machine learning model to do so. Identifying instances of narcissistic language within the analysed text data by making use of the trained model is another possibility for embodiments.
[00028] Using a sentiment analysis component to do an analysis of the emotional tenor of the written text data may be included in some implementations of the approach. The machine learning model may be trained in certain implementations by employing a tagged dataset of written text data that contains examples of narcissistic language. The instances of narcissistic language that have been found may, in certain implementations, be utilised to provide people individualised feedback on how they should improve their communication skills. The examples of narcissistic language that have been detected may, in certain implementations, be utilised to determine the possible dangers that may be linked with narcissistic behaviour in the workplace or in personal relationships.
[00029] 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.
[00030] Throughout 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).
[00031] 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.
[00032] 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.
[00033] 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 system for narcissist personality detection based on written text processing, comprising:
a text analysis module for parsing written text data, a machine learning module for training a model to detect narcissistic language patterns; and
a detection module for identifying narcissistic language in the analysed text data.

2. The system of claim 1, wherein the text analysis module uses natural language processing (NLP) techniques to analyse written text data and extract linguistic features such as word usage, sentence structure, and discourse coherence.

3. The system of claim 1, wherein the machine learning module uses supervised learning techniques to train a model to identify linguistic patterns associated with narcissistic personality traits.

4. The system of claim 1, wherein the detection module applies the trained model to the analysed text data to identify instances of narcissistic language.

5. The system of claim 1, wherein the text analysis module further includes a sentiment analysis component to identify the emotional tone of the written text data, and a visualization component to display the results of the analysis.

6. A method for narcissist personality detection based on written text processing, comprising: parsing written text data using natural language processing techniques; training a machine learning model to identify linguistic patterns associated with narcissistic personality traits; and identifying instances of narcissistic language in the analysed text data using the trained model.

7. The method of claim 6, further comprising analysing the emotional tone of the written text data using a sentiment analysis component.

8. The method of claim 7, wherein the machine learning model is trained using a labelled dataset of written text data that includes instances of narcissistic language.

9. The method of claim 7, wherein the identified instances of narcissistic language are used to provide personalized feedback to individuals on their communication style.

10. The method of claim 7, wherein the identified instances of narcissistic language are used to identify potential risks associated with narcissistic behaviour in the workplace or in personal relationships.

NARCISSIST PERSONALITY DETECTION BASED ON LANGUAGE PARSING
Abstract
A system for narcissist personality detection based on written text processing may be included in some embodiments of the present disclosure. This system may include a text analysis module for parsing written text data, a machine learning module for training a model to detect narcissistic language patterns, and a detection module for identifying narcissistic language in the analysed text data.

Fig. 1 , Claims:Claims
I/We Claim:
1. A system for narcissist personality detection based on written text processing, comprising:
a text analysis module for parsing written text data, a machine learning module for training a model to detect narcissistic language patterns; and
a detection module for identifying narcissistic language in the analysed text data.

2. The system of claim 1, wherein the text analysis module uses natural language processing (NLP) techniques to analyse written text data and extract linguistic features such as word usage, sentence structure, and discourse coherence.

3. The system of claim 1, wherein the machine learning module uses supervised learning techniques to train a model to identify linguistic patterns associated with narcissistic personality traits.

4. The system of claim 1, wherein the detection module applies the trained model to the analysed text data to identify instances of narcissistic language.

5. The system of claim 1, wherein the text analysis module further includes a sentiment analysis component to identify the emotional tone of the written text data, and a visualization component to display the results of the analysis.

6. A method for narcissist personality detection based on written text processing, comprising: parsing written text data using natural language processing techniques; training a machine learning model to identify linguistic patterns associated with narcissistic personality traits; and identifying instances of narcissistic language in the analysed text data using the trained model.

7. The method of claim 6, further comprising analysing the emotional tone of the written text data using a sentiment analysis component.

8. The method of claim 7, wherein the machine learning model is trained using a labelled dataset of written text data that includes instances of narcissistic language.

9. The method of claim 7, wherein the identified instances of narcissistic language are used to provide personalized feedback to individuals on their communication style.

10. The method of claim 7, wherein the identified instances of narcissistic language are used to identify potential risks associated with narcissistic behaviour in the workplace or in personal relationships.