We present a unique collection of four data sets to study social behaviou"/>

Combining sensors and surveys to study social interactions: A case of four science conferences

Personality science(2023)

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<p xmlns="http://www.ncbi.nlm.nih.gov/JATS1">We present a unique collection of four data sets to study social behaviour, collected during international scientific conferences. Interactions between participants were tracked using the SocioPatterns platform, which allows collecting face-to-face physical proximity events every 20 seconds. Through accompanying surveys, we gathered extensive information about the participants: sociodemographic characteristics, Big Five personality traits, DIAMONDS situation perceptions, measure of scientific attractiveness, motivations for attending the conferences, and perceptions of the crowd. Linking the sensor and survey data provides a rich window into social behaviour. At the individual level, the data sets allow personality scientists to investigate individual differences in social behaviour and pinpoint which individual characteristics (e.g., social roles, personality traits, situation perceptions) drive these individual differences. At the group level, the data allow to study the mechanisms responsible for interacting patterns within a scientific crowd during a social, networking and idea-sharing event.</div><span class="a-aminer-core-pub-c-paper-abstract-morebtn"><span>更多</span></span></div></div><div class="a-aminer-core-pub-c-paper-abstract-tranText">查看译文</div></div></div></div></span></div></div><div class="a-aminer-core-pub-index-titleBox"><div class="a-aminer-core-pub-index-keyTitle">关键词</div><div class="a-aminer-core-pub-index-titleKeys"><span>social interactions<!-- -->,</span><span>surveys<!-- -->,</span><span>sensors</span></div></div></div><div class="background" style="margin-top:16px;margin-bottom:16px" id="summary"><div class="mainTitle"><span>AI 理解论文</span></div><div><div class="stitle" style="margin-top:16px;margin-bottom:16px"><span>溯源树</span></div><div class="a-aminer-core-pub-index-renderTree"><div class="a-aminer-core-pub-index-example"><div class="a-aminer-core-pub-index-topExampleText"><span>样例</span></div><img src="https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg" alt=""/></div><div class="a-aminer-core-pub-index-layer"></div><div class="a-aminer-core-pub-index-pdfLoad"><div class="a-aminer-core-pub-index-pdfLoad_text"><span style="margin-right:24px"><svg class="icon" aria-hidden="true"><use xlink:href="#icon-suyuansu"></use></svg></span><span>生成溯源树,研究论文发展脉络</span></div></div></div></div></div></section><div><div class=""><section class="a-aminer-core-pub-index-rightBar"><div class="a-aminer-core-pub-index-commented "><div class="a-aminer-core-pub-index-bg"></div><div class="a-aminer-core-pub-index-title">Chat Paper</div><div class="a-core-home2-c-card-person-bottom-card-new-summary-index-summaryBox a-core-home2-c-card-person-bottom-card-new-summary-index-pubBox"><div class="a-core-home2-c-card-person-bottom-card-new-summary-index-loadingBox"><span class="a-core-home2-c-card-person-bottom-card-new-summary-index-loadingText">正在生成论文摘要</span><div class="ant-spin ant-spin-spinning"><i aria-label="icon: loading" style="font-size:24px" class="anticon anticon-loading ant-spin-dot"><svg viewBox="0 0 1024 1024" focusable="false" class="anticon-spin" data-icon="loading" width="1em" height="1em" fill="currentColor" aria-hidden="true"><path d="M988 548c-19.9 0-36-16.1-36-36 0-59.4-11.6-117-34.6-171.3a440.45 440.45 0 0 0-94.3-139.9 437.71 437.71 0 0 0-139.9-94.3C629 83.6 571.4 72 512 72c-19.9 0-36-16.1-36-36s16.1-36 36-36c69.1 0 136.2 13.5 199.3 40.3C772.3 66 827 103 874 150c47 47 83.9 101.8 109.7 162.7 26.7 63.1 40.2 130.2 40.2 199.3.1 19.9-16 36-35.9 36z"></path></svg></i></div></div></div></div></section></div></div></article></main></main></section></div> <script> window.g_useSSR = true; window.g_initialProps = {"global":{"collapsed":false,"preventRender":false,"isCompanyIp":false},"pub":{"paper":{"abstract":"\u003Ctitle xmlns=\"http:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002FJATS1\" \u002F\u003E \u003Cp xmlns=\"http:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002FJATS1\"\u003EWe present a unique collection of four data sets to study social behaviour, collected during international scientific conferences. Interactions between participants were tracked using the SocioPatterns platform, which allows collecting face-to-face physical proximity events every 20 seconds. Through accompanying surveys, we gathered extensive information about the participants: sociodemographic characteristics, Big Five personality traits, DIAMONDS situation perceptions, measure of scientific attractiveness, motivations for attending the conferences, and perceptions of the crowd. Linking the sensor and survey data provides a rich window into social behaviour. At the individual level, the data sets allow personality scientists to investigate individual differences in social behaviour and pinpoint which individual characteristics (e.g., social roles, personality traits, situation perceptions) drive these individual differences. 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