{
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  "Package": "webtrackR",
  "Title": "Preprocessing and Analyzing Web Tracking Data",
  "Version": "0.3.2",
  "Authors@R": "c(\nperson(\"David\", \"Schoch\", email = \"david@schochastics.net\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-2952-4812\")),\nperson(\"Bernhard\", \"Clemm von Hohenberg\", email = \"bernhard.clemm@gesis.org\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-6976-9745\")),\nperson(\"Frank\", \"Mangold\", email = \"frank.mangold@gesis.org\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-9776-3113\")),\nperson(\"Sebastian\", \"Stier\", email = \"sebastian.stier@gesis.org\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-1217-5778\")),\nperson(\"Maximilian\", \"Haag\", email = \"maximilian.haag@gesis.org\", role = \"ctb\",\ncomment = c(ORCID = \"0000-0002-0334-9270\"))\n)",
  "Description": "Data structures and methods to work with web tracking\ndata. The functions cover data preprocessing steps, enriching\nweb tracking data with external information and methods for the\nanalysis of digital behavior as used in several academic papers\n(e.g., Clemm von Hohenberg et al., 2023\n<doi:10.17605/OSF.IO/M3U9P>; Stier et al., 2022\n<doi:10.1017/S0003055421001222>).",
  "URL": "https://github.com/gesistsa/webtrackR",
  "BugReports": "https://github.com/gesistsa/webtrackR/issues",
  "License": "MIT + file LICENSE",
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  "Repository": "https://gesistsa.r-universe.dev",
  "Date/Publication": "2026-02-17 11:21:23 UTC",
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  "Packaged": {
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  "Author": "David Schoch [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-2952-4812>),\nBernhard Clemm von Hohenberg [aut] (ORCID:\n<https://orcid.org/0000-0002-6976-9745>),\nFrank Mangold [aut] (ORCID: <https://orcid.org/0000-0002-9776-3113>),\nSebastian Stier [aut] (ORCID: <https://orcid.org/0000-0002-1217-5778>),\nMaximilian Haag [ctb] (ORCID: <https://orcid.org/0000-0002-0334-9270>)",
  "Maintainer": "David Schoch <david@schochastics.net>",
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  "_created": "2026-05-23T08:35:01.000Z",
  "_published": "2026-05-23T08:38:00.122Z",
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    "add_panelist_data",
    "add_previous_visit",
    "add_referral",
    "add_session",
    "add_title",
    "as.wt_dt",
    "atkinson_index",
    "classify_visits",
    "create_urldummy",
    "deduplicate",
    "dissimilarity_index",
    "drop_query",
    "extract_domain",
    "extract_host",
    "extract_path",
    "extract_query",
    "is.wt_dt",
    "isolation_index",
    "parse_path",
    "sum_activity",
    "sum_durations",
    "sum_visits"
  ],
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      "object": "bakshy",
      "class": [
        "data.table",
        "data.frame"
      ],
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        "avg_align",
        "l2",
        "l1",
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        "r1",
        "r2"
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      "table": true,
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        "data.frame"
      ],
      "fields": [
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        "type"
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      "table": true,
      "tojson": true
    },
    {
      "name": "fake_tracking",
      "title": "Fake data",
      "object": "fake_tracking",
      "class": [
        "data.frame"
      ],
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        "panelist_id",
        "url",
        "timestamp"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    },
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      "name": "news_types",
      "title": "News Types",
      "object": "news_types",
      "class": [
        "data.table",
        "data.frame"
      ],
      "fields": [
        "domain",
        "type"
      ],
      "rows": 690,
      "table": true,
      "tojson": true
    },
    {
      "name": "testdt_survey_l",
      "title": "Test survey",
      "object": "testdt_survey_l",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "panelist_id",
        "age",
        "gender",
        "education",
        "leftright",
        "wave",
        "opinion"
      ],
      "rows": 15,
      "table": true,
      "tojson": true
    },
    {
      "name": "testdt_survey_w",
      "title": "Test survey",
      "object": "testdt_survey_w",
      "class": [
        "data.frame"
      ],
      "fields": [
        "panelist_id",
        "age",
        "gender",
        "education",
        "leftright",
        "opinion_w1",
        "opinion_w2",
        "opinion_w3"
      ],
      "rows": 5,
      "table": true,
      "tojson": true
    },
    {
      "name": "testdt_tracking",
      "title": "Test data",
      "object": "testdt_tracking",
      "class": [
        "data.frame"
      ],
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        "wave",
        "timestamp",
        "url",
        "device"
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      "rows": 49612,
      "table": true,
      "tojson": true
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  "_help": [
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      "page": "add_duration",
      "title": "Add time spent on a visit in seconds",
      "topics": [
        "add_duration"
      ]
    },
    {
      "page": "add_next_visit",
      "title": "Add the next visit as a new column",
      "topics": [
        "add_next_visit"
      ]
    },
    {
      "page": "add_panelist_data",
      "title": "Add panelist features to tracking data",
      "topics": [
        "add_panelist_data"
      ]
    },
    {
      "page": "add_previous_visit",
      "title": "Add the previous visit as a new column",
      "topics": [
        "add_previous_visit"
      ]
    },
    {
      "page": "add_referral",
      "title": "Add social media referrals as a new column",
      "topics": [
        "add_referral"
      ]
    },
    {
      "page": "add_session",
      "title": "Add a session variable",
      "topics": [
        "add_session"
      ]
    },
    {
      "page": "add_title",
      "title": "Download and add the \"title\" of a URL",
      "topics": [
        "add_title"
      ]
    },
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      "title": "Symmetric Atkinson Index calculates the symmetric Atkinson index",
      "topics": [
        "atkinson_index"
      ]
    },
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      "page": "bakshy",
      "title": "Bakshy Top500 Ideological alignment of 500 domains based on facebook data",
      "topics": [
        "bakshy"
      ]
    },
    {
      "page": "classify_visits",
      "title": "Classify visits by matching to a list of classes",
      "topics": [
        "classify_visits"
      ]
    },
    {
      "page": "create_urldummy",
      "title": "Create an urldummy variable",
      "topics": [
        "create_urldummy"
      ]
    },
    {
      "page": "deduplicate",
      "title": "Deduplicate visits",
      "topics": [
        "deduplicate"
      ]
    },
    {
      "page": "dissimilarity_index",
      "title": "Dissimilarity Index",
      "topics": [
        "dissimilarity_index"
      ]
    },
    {
      "page": "domain_list",
      "title": "Domain list classification of domains into news,portals, search, and social media",
      "topics": [
        "domain_list"
      ]
    },
    {
      "page": "drop_query",
      "title": "Drop the query and fragment from URL",
      "topics": [
        "drop_query"
      ]
    },
    {
      "page": "extract_domain",
      "title": "Extract the domain from URL",
      "topics": [
        "extract_domain"
      ]
    },
    {
      "page": "extract_host",
      "title": "Extract the host from URL",
      "topics": [
        "extract_host"
      ]
    },
    {
      "page": "extract_path",
      "title": "Extract the path from URL",
      "topics": [
        "extract_path"
      ]
    },
    {
      "page": "extract_query",
      "title": "Extract the query from URL",
      "topics": [
        "extract_query"
      ]
    },
    {
      "page": "fake_tracking",
      "title": "Fake data",
      "topics": [
        "fake_tracking"
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    },
    {
      "page": "isolation_index",
      "title": "Isolation Index",
      "topics": [
        "isolation_index"
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    },
    {
      "page": "news_types",
      "title": "News Types",
      "topics": [
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      ]
    },
    {
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      "title": "Parse parts of path for text analysis",
      "topics": [
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      ]
    },
    {
      "page": "print.wt_dt",
      "title": "Print web tracking data",
      "topics": [
        "print.wt_dt"
      ]
    },
    {
      "page": "sum_activity",
      "title": "Summarize activity per person",
      "topics": [
        "sum_activity"
      ]
    },
    {
      "page": "sum_durations",
      "title": "Summarize visit duration by person",
      "topics": [
        "sum_durations"
      ]
    },
    {
      "page": "sum_visits",
      "title": "Summarize number of visits by person",
      "topics": [
        "sum_visits"
      ]
    },
    {
      "page": "summary.wt_dt",
      "title": "Summary function for web tracking data",
      "topics": [
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    {
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      ]
    },
    {
      "page": "testdt_tracking",
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      "topics": [
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      ]
    },
    {
      "page": "vars_exist",
      "title": "Check if columns are present",
      "topics": [
        "vars_exist"
      ]
    },
    {
      "page": "wt_dt",
      "title": "An S3 class to store web tracking data",
      "topics": [
        "as.wt_dt",
        "is.wt_dt",
        "wt_dt"
      ]
    }
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