Article Instance

HTTP 200 OK
Allow: GET
Content-Type: application/json
Vary: Accept

{
    "pk": 27273,
    "title": "The strategic advantages of micro-targeted campaigning: A proof of principleBayesian Agent-Based Model",
    "subtitle": null,
    "abstract": "Predicting the effect of persuasion campaigns is difficult, asbelief changes may cascade through a network. In recentyears, political campaigns have adopted micro-targetingstrategies that segment voters into fine-grained clusters formore specific targetting. At present, there is little evidencethat explores the efficiency of this method. Through anAgent-Based Model, the current paper provides a novelmethod for exploring predicted effects of strategic persuasioncampaigns.The voters in the model are rational and revise their beliefsin the propositions expounded by the politicians inaccordance with Bayesian belief updating through a sourcecredibility model.The model provides a proof of concept and shows strategicadvantages of micro-targeted campaigning. Despite havingonly little voter data allowing crude segmentation, the micro-targeted campaign consistently beat stochastic campaignswith the same reach. However, given substantially greaterreach, a positively perceived stochastic candidate can nullifyor beat a strategic persuasion campaigns.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Agent-Based Model; Persuasion; Strategiccampaigns; Politics; Voting simulation"
        }
    ],
    "section": "Posters: Papers",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/55f2z6rt",
    "frozenauthors": [
        {
            "first_name": "Jens",
            "middle_name": "Koed",
            "last_name": "Madsen",
            "name_suffix": "",
            "institution": "University of Oxford",
            "department": ""
        },
        {
            "first_name": "Toby",
            "middle_name": "D.",
            "last_name": "Pilditch",
            "name_suffix": "",
            "institution": "University College London",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2017-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27273/galley/16909/download/"
        }
    ]
}