{
    "article_id": 439,
    "public_id": "84256ab1-dcfc-4a2f-b066-2bb284705dc4",
    "internal_identifier": null,
    "source_identifier": "5:84",
    "status": "published",
    "type": "research_article",
    "title": "A Stochastic Binary Opinion Model",
    "title_secondary": null,
    "abstract": "With the development of technology and growth of social networking among individuals, the quantitative study of social dynamics has attracted a great interest from researchers. In this study, we propose a stochastic binary opinion model where agents are considered to hold an opinion of ``yes\" or ``no\" at each moment. In this model, the number of agents with opinion ``yes\" at time t  is considered to be a birth-death process, and the configuration of the opinions at each moment is determined by a probability distribution. The rate an agent changes his/her opinion depends on the influence of the group's current state on the agent, given with a social-impact function, and a scalar self-motivation coefficient. We analyze the stationary probabilities with regard to the social-impact function and the self- motivation coefficient. We present numerical results showing the cases of the dominance of an opinion as well as of balanced opinions. \r\n ",
    "language": "en",
    "english_title": null,
    "english_abstract": null,
    "doi": null,
    "doi_url": null,
    "resource_url": "https://www.set-science.com/a/84256ab1-dcfc-4a2f-b066-2bb284705dc4",
    "pdf_url": "https://www.set-science.com/a/84256ab1-dcfc-4a2f-b066-2bb284705dc4/pdf",
    "og_image": "https://www.set-science.com/assets/img/og-card-v2.png",
    "authors": [
        {
            "public_id": "6e23317e-b400-4a8c-8474-1c17c561da83",
            "given": "Serap",
            "family": "Tay \r\nStamoulas",
            "full": "Serap Tay \r\nStamoulas",
            "literal": null,
            "orcid": null,
            "orcid_url": null,
            "email": "serap.taystamoulas@dicle.edu.tr",
            "corresponding": true,
            "sequence": "first",
            "affiliations": [
                {
                    "name": "Department of Mathematics, Dicle University ",
                    "department": null,
                    "country": null,
                    "country_code": null,
                    "ror": null,
                    "ror_url": null
                }
            ]
        },
        {
            "public_id": "2d592c07-3621-4f56-95bf-49598456fd5f",
            "given": "Muruhan ",
            "family": "Rathinam ",
            "full": "Muruhan  Rathinam ",
            "literal": null,
            "orcid": null,
            "orcid_url": null,
            "email": "muruhan@umbc.edu",
            "corresponding": false,
            "sequence": "additional",
            "affiliations": [
                {
                    "name": "Department of Mathematics, University of Maryland ",
                    "department": null,
                    "country": null,
                    "country_code": null,
                    "ror": null,
                    "ror_url": null
                }
            ]
        }
    ],
    "keywords": [
        "Social Dynamics, Stochastic Models, Asymptotic analysis"
    ],
    "translations": [
        {
            "language": "en",
            "title": "A Stochastic Binary Opinion Model",
            "abstract": "With the development of technology and growth of social networking among individuals, the quantitative study of social dynamics has attracted a great interest from researchers. In this study, we propose a stochastic binary opinion model where agents are considered to hold an opinion of ``yes\" or ``no\" at each moment. In this model, the number of agents with opinion ``yes\" at time t  is considered to be a birth-death process, and the configuration of the opinions at each moment is determined by a probability distribution. The rate an agent changes his/her opinion depends on the influence of the group's current state on the agent, given with a social-impact function, and a scalar self-motivation coefficient. We analyze the stationary probabilities with regard to the social-impact function and the self- motivation coefficient. We present numerical results showing the cases of the dominance of an opinion as well as of balanced opinions. \r\n  \r\n\r\n",
            "keywords": [
                "Social Dynamics, Stochastic Models, Asymptotic analysis"
            ]
        }
    ],
    "subjects": [],
    "subject_names": [],
    "published_date": "2018-06-23",
    "published_year": "2018",
    "received_date": null,
    "accepted_date": null,
    "volume": "2",
    "issue": null,
    "page_first": "89",
    "page_last": "89",
    "article_number": null,
    "conference": {
        "short_name": "ISAS 2018",
        "full_title": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "name": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "acronym": "ISAS 2018",
        "location": "Kemer-Antalya, Türkiye",
        "start_date": "2018-04-11",
        "end_date": null,
        "public_id": "1d94fec9-c4fe-4034-9157-0b205eef4e56"
    },
    "proceedings": {
        "title": "Ist International Symposium on Innovative Approaches in Scientific Studies",
        "series_title": "Setsci conference indexing system",
        "publisher": "SET Technology",
        "isbn": null,
        "eisbn": null,
        "issn": "2618-6446",
        "eissn": null,
        "doi": null,
        "doi_prefix": null,
        "slug": "setsci-volume-2-2018-legacy-5",
        "public_id": "03da7b1c-cb6e-4f3b-aee4-ac41ee60fd75",
        "url": "https://www.set-science.com/p/setsci-volume-2-2018-legacy-5"
    },
    "license": {
        "name": "CC BY 4.0",
        "url": "https://creativecommons.org/licenses/by/4.0/",
        "code": "CC-BY-4.0",
        "open_access": true
    },
    "copyright": {
        "holder": "SET Technology",
        "year": "2018"
    },
    "funding_statement": null,
    "funders": [],
    "references": [],
    "statements": {
        "acknowledgements": null,
        "conflict_of_interest": null,
        "data_availability": null,
        "ai_disclosure": null
    },
    "credit": [],
    "history": {
        "published": "2018-06-23"
    }
}