发布求助
文献互助 智能选刊 最新文献

WCPR '14最新文献

筛选
英文 中文
A Multivariate Regression Approach to Personality Impression Recognition of Vloggers 视频博主人格印象识别的多元回归方法
WCPR '14 Pub Date : 2014-11-07 DOI: 10.1145/2659522.2659526
G. Farnadi, Shanu Sushmita, Geetha Sitaraman, Nhat Ton, M. D. Cock, S. Davalos
{"title":"A Multivariate Regression Approach to Personality Impression Recognition of Vloggers","authors":"G. Farnadi, Shanu Sushmita, Geetha Sitaraman, Nhat Ton, M. D. Cock, S. Davalos","doi":"10.1145/2659522.2659526","DOIUrl":"https://doi.org/10.1145/2659522.2659526","url":null,"abstract":"Research in psychology has suggested that behavior of individuals can be explained to a great extent by their underlying personality traits. In this paper, we focus on predicting how the personality of YouTube video bloggers is perceived by their viewers. Our approach to personality recognition is multimodal in the sense that we use audio-video features, as well as textual (emotional and linguistic) features extracted from the transcripts of vlogs. Based on these features, we predict the extent to which the video blogger is perceived to exhibit each of the traits of the Big Five personality model. In addition, we explore 5 multivariate regression techniques and contrast them with a single target approach for predicting personality impression scores. All 6 algorithms are able to outperform the average baseline model for all 5 personality traits on a dataset of 404 YouTube videos. This is interesting because previously published methods for the same dataset show an improvement over the baseline for the majority of personality traits, but not for all simultaneously.","PeriodicalId":423934,"journal":{"name":"WCPR '14","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132681498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 32
Feature Analysis for Computational Personality Recognition Using YouTube Personality Data set 基于YouTube人格数据集的计算人格识别特征分析
WCPR '14 Pub Date : 2014-11-07 DOI: 10.1145/2659522.2659528
Chandrima Sarkar, S. Bhatia, Arvind Agarwal, Juan Li
{"title":"Feature Analysis for Computational Personality Recognition Using YouTube Personality Data set","authors":"Chandrima Sarkar, S. Bhatia, Arvind Agarwal, Juan Li","doi":"10.1145/2659522.2659528","DOIUrl":"https://doi.org/10.1145/2659522.2659528","url":null,"abstract":"It is an important yet challenging task to develop an intelligent system in a way that it automatically classifies human personality traits. Automatic classification of human traits requires the knowledge of significant attributes and features that contribute to the prediction of a given trait. Motivated by the fact that detection of significant features is an essential part of a personality recognition system, we present in this paper an in-depth analysis of audio visual, text, demographic and sentiment features for classification of multi-modal personality traits namely, extraversion, agreeableness, conscientiousness, emotional stability and openness to experience. We use the YouTube personality data set and use logistic regression model with a ridge estimator for the classification purpose. We experiment with audio-visual features, bag of word features, sentiment based and demographic features. Our results provide important insights about the significance of different feature types for personality classification task.","PeriodicalId":423934,"journal":{"name":"WCPR '14","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133964476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 57
Evaluating Content-Independent Features for Personality Recognition 评估与内容无关的个性识别特征
WCPR '14 Pub Date : 2014-11-07 DOI: 10.1145/2659522.2659527
B. Verhoeven, Juan Soler, Walter Daelemans
{"title":"Evaluating Content-Independent Features for Personality Recognition","authors":"B. Verhoeven, Juan Soler, Walter Daelemans","doi":"10.1145/2659522.2659527","DOIUrl":"https://doi.org/10.1145/2659522.2659527","url":null,"abstract":"This paper describes our submission for the WCPR14 shared task on computational personality recognition. We have investigated whether the features proposed by Soler and Wanner (2014) for gender prediction might also be useful in personality recognition. We have compared these features with simple approaches using token unigrams, character trigrams and liwc features. Although the newly investigated features seem to work quite well on certain personality traits, they do not outperform the simple approaches.","PeriodicalId":423934,"journal":{"name":"WCPR '14","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117026325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Look! Who's Talking?: Projection of Extraversion Across Different Social Contexts 看！谁说的?外向性在不同社会背景下的投射
WCPR '14 Pub Date : 2014-11-07 DOI: 10.1145/2659522.2659530
Scott Nowson, Alastair J. Gill
{"title":"Look! Who's Talking?: Projection of Extraversion Across Different Social Contexts","authors":"Scott Nowson, Alastair J. Gill","doi":"10.1145/2659522.2659530","DOIUrl":"https://doi.org/10.1145/2659522.2659530","url":null,"abstract":"Automatic classification of personality from language depends upon large quantities of relevant training data, which raises two potential problems. First, collecting personality information from the author or speaker can be invasive and expensive, especially in sensitive contexts. Second, issues of context or genre can reduce the usefulness of available training resources for broader personality classification. One approach to dealing with the first issue is to use external judges rather than the text's author. In this paper, we test the extent to which these personality perceptions are useful for training a classifier between different linguistic genres. Following disappointing cross-training results, we explore the projection of personality through specific linguistic factors. We find that while some differences are between the genres overall, some indicate that indeed personality is evidenced differently across situations. It is clear that care is needed leveraging resources from different domains for computational personality recognition.","PeriodicalId":423934,"journal":{"name":"WCPR '14","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122741753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 21
The Impact of Affective Verbal Content on Predicting Personality Impressions in YouTube Videos 情感性言语内容对预测YouTube视频中人格印象的影响
WCPR '14 Pub Date : 2014-11-07 DOI: 10.1145/2659522.2659529
S. Gievska, Kiril Koroveshovski
{"title":"The Impact of Affective Verbal Content on Predicting Personality Impressions in YouTube Videos","authors":"S. Gievska, Kiril Koroveshovski","doi":"10.1145/2659522.2659529","DOIUrl":"https://doi.org/10.1145/2659522.2659529","url":null,"abstract":"Human nature as always implies massive challenges for predictive modeling that are yet to be fully explored. In this paper, we report on an experiment that examines the predictive effect of the gender and the affective content of video transcripts on predicting personality impressions of the person being judged. While gender had positive impact on the predictability across all personality traits, the effects of the emotional features varied across traits. Coarse-grain emotional categories resulted in performance gains for Agreeableness and Neuroticism, while the inclusion of fine-grain emotional features had more positive effect on predicting Extroversion and Openness to Experiences. The initial results are encouraging and comparable to related research.","PeriodicalId":423934,"journal":{"name":"WCPR '14","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127815559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
Predicting Personality Traits using Multimodal Information 利用多模态信息预测人格特征
WCPR '14 Pub Date : 2014-11-07 DOI: 10.1145/2659522.2659531
Firoj Alam, G. Riccardi
{"title":"Predicting Personality Traits using Multimodal Information","authors":"Firoj Alam, G. Riccardi","doi":"10.1145/2659522.2659531","DOIUrl":"https://doi.org/10.1145/2659522.2659531","url":null,"abstract":"Measuring personality traits has a long story in psychology where analysis has been done by asking sets of questions. These question sets (inventories) have been designed by investigating lexical terms that we use in our daily communications or by analyzing biological phenomena. Whether consciously or unconsciously we express our thoughts and behaviors when communicating with others, either verbally, non-verbally or using visual expressions. Recently, research in behavioral signal processing has focused on automatically measuring personality traits using different behavioral cues that appear in our daily communication. In this study, we present an approach to automatically recognize personality traits using a video-blog (vlog) corpus, consisting of transcription and extracted audio-visual features. We analyzed linguistic, psycholinguistic and emotional features in addition to the audio-visual features provided with the dataset. We also studied whether we can better predict a trait by identifying other traits. Using our best models we obtained very promising results compared to the official baseline.","PeriodicalId":423934,"journal":{"name":"WCPR '14","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116751155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 68
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信