{
    "paper_id": "W12-0400",
    "header": {
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        "date_generated": "2023-01-19T04:14:39.356700Z"
    },
    "title": "",
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    "year": "",
    "venue": null,
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    "abstract": "",
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        "paper_id": "W12-0400",
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        "abstract": [],
        "body_text": [
            {
                "text": "Welcome to the EACL-2012 Workshop on Computational Approaches to Deception Detection. In organizing the workshop, we hope that it will allow us to review the foundations of this relatively new subfield with computational linguistics and encourage more work in the area.",
                "cite_spans": [],
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                "section": "Introduction",
                "sec_num": null
            },
            {
                "text": "For much of the twentieth century, the fields of psychology and criminal justice have studied the behaviors that might be associated, directly or indirectly, with deception. Three types of behavior have been examined: facial expressions and body movements; vocal behaviors, including prosodic features; and verbal behaviors, including the words and structures that might correlate with deception.",
                "cite_spans": [],
                "ref_spans": [],
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                "section": "Introduction",
                "sec_num": null
            },
            {
                "text": "Now is a good time to review the NLP approaches that have been tried, and to consider the foundations and trends, both theoretical and applied, that will enable us to move forward productively. Several areas of natural language processing are ripe to address the vocal and verbal features that might be associated with deception and new approaches may well combine information from all three modalities. A spate of recent NLP papers on the classification of narratives as truthful or deceptive suggests that the field is ready to open up to this promising area. We see some trends in deception research, expressed in the current collection of papers by descriptions of stylometric techniques, sensor technologies, machine learning approaches and models of data collection and processing.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Introduction",
                "sec_num": null
            },
            {
                "text": "We are pleased at the interest in the workshop represented by the 14 high quality submissions we received. The committee accepted 9 as papers, 3 as posters, and two as demos. Among these are papers that will help us define the parameters of the field, build collections to test approaches, and create novel applications. We are especially pleased by the presence of cross-linguistic studies and the prospect of future work that extends deception research to a range of cross-cultural and cross-linguistic contexts.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Introduction",
                "sec_num": null
            },
            {
                "text": "We would like to thank EACL for its endorsement of the workshop. We would also like to thank the EACL workshop co-chairs, Kristiina Jokinen and Alessandro Moschitti, for their support. Most of all, we would like to thank our enthusiastic program committee members for their timely and thoughtful review comments. Without them, this workshop on Computational Approaches to Deception Detection could not be implemented successfully.",
                "cite_spans": [],
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                "eq_spans": [],
                "section": "Introduction",
                "sec_num": null
            },
            {
                "text": "Eileen Fitzpatrick, Montclair State University Joan Bachenko, Linguistech Consortium Tommaso Fornaciari, University of Trento",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Organizers:",
                "sec_num": null
            }
        ],
        "back_matter": [],
        "bib_entries": {
            "BIBREF1": {
                "ref_id": "b1",
                "title": "Session 4: Posters Let's Lie Together: Co-Presence Effects on Children's Deceptive Skills Marc Swerts Argument Formation in the Reasoning Process: Toward a Generic Model of Deception Detection",
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                "year": null,
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                "num": null,
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                "raw_text": "Session W3: (15:30) Session 4: Posters Let's Lie Together: Co-Presence Effects on Children's Deceptive Skills Marc Swerts Argument Formation in the Reasoning Process: Toward a Generic Model of Deception Detection Deqing Li and Eugene Santos",
                "links": null
            },
            "BIBREF2": {
                "ref_id": "b2",
                "title": "Vlad Niculae and Maria-Octavia Sulea Making the Subjective Objective? Computer-Assisted Quantification of Qualitative Content Cues to Deception Siegfried Ludwig Sporer Modelling Fixated Discourse in Chats with Cyberpedophiles Dasha Bogdanova",
                "authors": [],
                "year": null,
                "venue": "Pastiche Detection Based on Stopword Rankings. Exposing Impersonators of a Romanian Writer Liviu P. Dinu",
                "volume": "3",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Pastiche Detection Based on Stopword Rankings. Exposing Impersonators of a Romanian Writer Liviu P. Dinu, Vlad Niculae and Maria-Octavia Sulea Making the Subjective Objective? Computer-Assisted Quantification of Qualitative Con- tent Cues to Deception Siegfried Ludwig Sporer Modelling Fixated Discourse in Chats with Cyberpedophiles Dasha Bogdanova, Paolo Rosso and Thamar Solorio Session W3: (16:30) Session 5",
                "links": null
            },
            "BIBREF3": {
                "ref_id": "b3",
                "title": "Detecting Stylistic Deception Patrick Juola Identification of Truth and Deception in Text: Application of Vector Space Model to Rhetorical Structure Theory Victoria L. Rubin and Tatiana Vashchilko",
                "authors": [],
                "year": null,
                "venue": "",
                "volume": "",
                "issue": "",
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                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Detecting Stylistic Deception Patrick Juola Identification of Truth and Deception in Text: Application of Vector Space Model to Rhetorical Structure Theory Victoria L. Rubin and Tatiana Vashchilko",
                "links": null
            }
        },
        "ref_entries": {}
    }
}