Human Communication Dynamics in Digital Footsteps: A Study of the Agreement between Self-Reported Ties and Email Networks
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{"title"=>"Human communication dynamics in digital footsteps: A study of the agreement between self-reported ties and email networks", "type"=>"journal", "authors"=>[{"first_name"=>"Stefan", "last_name"=>"Wuchty", "scopus_author_id"=>"6602576457"}, {"first_name"=>"Brian", "last_name"=>"Uzzi", "scopus_author_id"=>"6603149512"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"22114665", "sgr"=>"81255128915", "doi"=>"10.1371/journal.pone.0026972", "scopus"=>"2-s2.0-81255128915", "pui"=>"362939828", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "issn"=>"19326203"}, "id"=>"7ce98162-09eb-31fd-ac74-74bc60c06ebb", "abstract"=>"Digital communication data has created opportunities to advance the knowledge of human dynamics in many areas, including national security, behavioral health, and consumerism. While digital data uniquely captures the totality of a person's communication, past research consistently shows that a subset of contacts makes up a person's \"social network\" of unique resource providers. To address this gap, we analyzed the correspondence between self-reported social network data and email communication data with the objective of identifying the dynamics in e-communication that correlate with a person's perception of a significant network tie. First, we examined the predictive utility of three popular methods to derive social network data from email data based on volume and reciprocity of bilateral email exchanges. Second, we observed differences in the response dynamics along self-reported ties, allowing us to introduce and test a new method that incorporates time-resolved exchange data. Using a range of robustness checks for measurement and misreporting errors in self-report and email data, we find that the methods have similar predictive utility. Although e-communication has lowered communication costs with large numbers of persons, and potentially extended our number of, and reach to contacts, our case results suggest that underlying behavioral patterns indicative of friendship or professional contacts continue to operate in a classical fashion in email interactions.", "link"=>"http://www.mendeley.com/research/human-communication-dynamics-digital-footsteps-study-agreement-between-selfreported-ties-email-netwo", "reader_count"=>86, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>7, "Student > Doctoral Student"=>9, "Researcher"=>12, "Student > Ph. D. Student"=>21, "Student > Postgraduate"=>2, "Student > Master"=>15, "Other"=>2, "Student > Bachelor"=>9, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>2, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>7, "Student > Doctoral Student"=>9, "Researcher"=>12, "Student > Ph. D. Student"=>21, "Student > Postgraduate"=>2, "Student > Master"=>15, "Other"=>2, "Student > Bachelor"=>9, "Lecturer"=>3, "Lecturer > Senior Lecturer"=>2, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>5, "Agricultural and Biological Sciences"=>1, "Philosophy"=>1, "Business, Management and Accounting"=>14, "Computer Science"=>12, "Economics, Econometrics and Finance"=>2, "Engineering"=>1, "Environmental Science"=>2, "Nursing and Health Professions"=>2, "Mathematics"=>2, "Medicine and Dentistry"=>3, "Sports and Recreations"=>1, "Physics and Astronomy"=>4, "Psychology"=>8, "Social Sciences"=>28}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Social Sciences"=>{"Social Sciences"=>28}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>4}, "Psychology"=>{"Psychology"=>8}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>5}, "Environmental Science"=>{"Environmental Science"=>2}, "Engineering"=>{"Engineering"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Computer Science"=>{"Computer Science"=>12}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>14}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"Canada"=>1, "United States"=>3, "Japan"=>2, "Italy"=>1, "United Kingdom"=>1, "Australia"=>1, "Portugal"=>1, "Germany"=>4, "Spain"=>1}, "group_count"=>1}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/711548"], "description"=>"<p>(<b>A</b>) Counting the number of email messages that flow between a pair of persons we observed a strong power-law. (<b>B</b>) In the distribution of social ties a person is involved in, we found 4.8±3.8 contacts per person (dashed line). (<b>C</b>) Utilizing our methods, we converted emails to social attachments. ROCs indicate good agreement levels<b>,</b> comparing predicted ties to self-reported contacts (Area Under the ROC Curve (AUC) criterion: Normalization Method AUC = 0.891, Reciprocation Method AUC = 0.867, and Total Volume Method AUC = 0.867). Utilizing total volume method (VM), we indicated best TPR = 76.7% and FPR = 18.2% values that corresponded to the maximum correlation threshold between self-reported and predicted ties by a square. Analogously, we found TPR = 83.6% and FPR = 22.7 utilizing the reciprocation method (RM) and TPR = 75.3% and FPR = 12.2% using the normalization method (NM).</p>", "links"=>[], "tags"=>["psychology", "Human relations", "Sociology", "Computational sociology", "social networks", "Sociometry", "characteristics", "roc", "curves"], "article_id"=>381904, "categories"=>["Sociology"], "users"=>["Stefan Wuchty", "Brian Uzzi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026972.g001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Data_characteristics_and_ROC_curves_of_conversion_methods_/381904", "title"=>"Data characteristics and ROC curves of conversion methods.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-11-17 00:31:44"}
  • {"files"=>["https://ndownloader.figshare.com/files/711615"], "description"=>"<p>In (<b>A</b>) we show results of validity tests of each method in the presence of measurement noise in the email data, where noise was simulated by randomly adding or deleting email messages in increments up to 50%. All the methods appear to be roughly robust to this type of measurement error. In (<b>B</b>) we randomly added false ties significantly lowering agreement. In (<b>C</b>) we randomly added self-reported ties, only if chosen persons share at least a certain number of common contacts as in real-life, recovering reliability.</p>", "links"=>[], "tags"=>["psychology", "Human relations", "Sociology", "Computational sociology", "social networks", "Sociometry", "robustness"], "article_id"=>381973, "categories"=>["Sociology"], "users"=>["Stefan Wuchty", "Brian Uzzi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026972.g002", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Noise_robustness_of_conversion_methods_/381973", "title"=>"Noise robustness of conversion methods.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-11-17 00:32:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/711713"], "description"=>"<p>In (<b>A</b>) we show a profile of emails that were exchanged along social and professional ties. Non-ties referred to pairs of individuals that exchanged emails but were not self-reported as contacts. (<b>B</b>) Frequency distributions of response times (mean  =  dotted lines) of different types of ties indicate that social friendship ties had the lowest response time. (<b>C</b>) Discriminating between self-reported ties and non-ties using the normalization method, we determined the weight of emails that were exchanged in a certain time interval. We observed that emails sent within the same day contributed significantly to the discrimination of social and professional ties from non-ties. Determining weight difference, emails exchanged in short intervals predominantly characterize social friendship ties while emails that were sent with up to 8 days delay had a higher impact on the discrimination of professional ties (inset).</p>", "links"=>[], "tags"=>["psychology", "Human relations", "Sociology", "Computational sociology", "social networks", "Sociometry"], "article_id"=>382072, "categories"=>["Sociology"], "users"=>["Stefan Wuchty", "Brian Uzzi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0026972.g003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Time_resolved_data_characteristics_/382072", "title"=>"Time-resolved data characteristics.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-11-17 00:34:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/360549", "https://ndownloader.figshare.com/files/360586", "https://ndownloader.figshare.com/files/360625", "https://ndownloader.figshare.com/files/360665", "https://ndownloader.figshare.com/files/360702", "https://ndownloader.figshare.com/files/360763", "https://ndownloader.figshare.com/files/360808", "https://ndownloader.figshare.com/files/360843"], "description"=>"<div><p>Digital communication data has created opportunities to advance the knowledge of human dynamics in many areas, including national security, behavioral health, and consumerism. While digital data uniquely captures the totality of a person's communication, past research consistently shows that a subset of contacts makes up a person's “social network” of unique resource providers. To address this gap, we analyzed the correspondence between self-reported social network data and email communication data with the objective of identifying the dynamics in e-communication that correlate with a person's perception of a significant network tie. First, we examined the predictive utility of three popular methods to derive social network data from email data based on volume and reciprocity of bilateral email exchanges. Second, we observed differences in the response dynamics along self-reported ties, allowing us to introduce and test a new method that incorporates time-resolved exchange data. Using a range of robustness checks for measurement and misreporting errors in self-report and email data, we find that the methods have similar predictive utility. Although e-communication has lowered communication costs with large numbers of persons, and potentially extended our number of, and reach to contacts, our case results suggest that underlying behavioral patterns indicative of friendship or professional contacts continue to operate in a classical fashion in email interactions.</p> </div>", "links"=>[], "tags"=>["psychology", "Human relations", "Sociology", "Computational sociology", "social networks", "Sociometry", "self-reported", "ties", "email", "networks"], "article_id"=>131266, "categories"=>["Sociology"], "users"=>["Stefan Wuchty", "Brian Uzzi"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0026972.s001", "https://dx.doi.org/10.1371/journal.pone.0026972.s002", "https://dx.doi.org/10.1371/journal.pone.0026972.s003", "https://dx.doi.org/10.1371/journal.pone.0026972.s004", "https://dx.doi.org/10.1371/journal.pone.0026972.s005", "https://dx.doi.org/10.1371/journal.pone.0026972.s006", "https://dx.doi.org/10.1371/journal.pone.0026972.s007", "https://dx.doi.org/10.1371/journal.pone.0026972.s008"], "stats"=>{"downloads"=>25, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Human_Communication_Dynamics_in_Digital_Footsteps_A_Study_of_the_Agreement_between_Self_Reported_Ties_and_Email_Networks/131266", "title"=>"Human Communication Dynamics in Digital Footsteps: A Study of the Agreement between Self-Reported Ties and Email Networks", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-11-17 00:21:06"}

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Relative Metric

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