Summarising en-net online forum statistics

The ennet package also includes analytic functions that summarises the text data available from the en-net online forum. Currently, there are four analytic functions available from ennet:

Counting number of topics/questions

Summarising the number of topics or questions raised within the en-net online forum is basic and useful analytics that can proxy relative importance of a thematic area within the forum. This is facilitated using the count_topics function. Counting of topics is done per thematic area and by a specific time period. Counting of topics by month and year is performed by default:

get_themes() %>%
  get_themes_topics() %>%
  count_topics()

which results in:

#> # A tibble: 851 x 4
#>    Theme                                Month  Year     n
#>    <chr>                                <fct> <dbl> <int>
#>  1 Adolescent nutrition                 Jun    2018     6
#>  2 Adolescent nutrition                 Jul    2018     2
#>  3 Adolescent nutrition                 Feb    2020     1
#>  4 Adolescent nutrition                 May    2018     1
#>  5 Adolescent nutrition                 Jun    2020     1
#>  6 Adolescent nutrition                 Aug    2018     1
#>  7 Adolescent nutrition                 Sep    2018     1
#>  8 Announcements & Nutritionists needed Aug    2015    33
#>  9 Announcements & Nutritionists needed May    2019    26
#> 10 Announcements & Nutritionists needed Jun    2015    26
#> # … with 841 more rows

Counting of topics by year is specified as follows:

get_themes() %>%
  get_themes_topics() %>%
  count_topics(by_date = "year")

which results in:

#> # A tibble: 142 x 3
#>    Theme                                 Year     n
#>    <chr>                                <dbl> <int>
#>  1 Adolescent nutrition                  2018    11
#>  2 Adolescent nutrition                  2020     2
#>  3 Announcements & Nutritionists needed  2015   196
#>  4 Announcements & Nutritionists needed  2014   165
#>  5 Announcements & Nutritionists needed  2019   134
#>  6 Announcements & Nutritionists needed  2016   130
#>  7 Announcements & Nutritionists needed  2017   129
#>  8 Announcements & Nutritionists needed  2018   126
#>  9 Announcements & Nutritionists needed  2013   101
#> 10 Announcements & Nutritionists needed  2012    82
#> # … with 132 more rows

Counting of topics overall across the years is specified as follows:

get_themes() %>%
  get_themes_topics() %>%
  count_topics(by_date = "all")

which results in:

#> # A tibble: 18 x 2
#>    Theme                                                              n
#>    <chr>                                                          <int>
#>  1 Announcements & Nutritionists needed                            1229
#>  2 Management of wasting/acute malnutrition                         533
#>  3 Assessment and Surveillance                                      454
#>  4 Infant and young child feeding interventions                     196
#>  5 Coverage assessment                                               93
#>  6 Upcoming trainings                                                92
#>  7 COVID-19 and nutrition programming                                83
#>  8 Micronutrients                                                    54
#>  9 Other thematic area                                               51
#> 10 Scaling Up Nutrition (SUN)                                        51
#> 11 Cross-cutting issues                                              47
#> 12 Food assistance                                                   31
#> 13 Management of At Risk Mothers and Infants                         27
#> 14 Prevention and management of stunting                             21
#> 15 Partnerships for research                                         18
#> 16 Adolescent nutrition                                              13
#> 17 Simplified Approaches for the Management of Acute Malnutrition    10
#> 18 Multi-sector nutrition programming                                 3

By default, the output of count_topics arranges the results by descending frequency of counts of each topic by the grouping variable. This default behaviour can be changed by setting the .sorted argument to FALSE.

Counting number of topics/questions raised by an author

Summarising the number of topics or questions raised within the en-net online forum for each author is another basic and useful analytics that can proxy level of engagement by those participating in the forum. This is facilitated using the count_authors function. Counting of topics for each author is done per thematic area and by a specific time period. Counting of topics for each author by month and year is performed by default:

get_themes() %>%
  get_themes_topics() %>%
  count_authors()

which results in:

#> # A tibble: 2,513 x 5
#>    Theme                                Author           Month  Year     n
#>    <chr>                                <chr>            <fct> <dbl> <int>
#>  1 Announcements & Nutritionists needed Anonymous 1494   Jun    2015    13
#>  2 Announcements & Nutritionists needed Mark Hawkes      May    2019    13
#>  3 Announcements & Nutritionists needed Marie Lecuyer    May    2014    11
#>  4 Announcements & Nutritionists needed Anonymous 1271   May    2012     9
#>  5 Announcements & Nutritionists needed Anonymous 1494   Aug    2015     9
#>  6 COVID-19 and nutrition programming   GTAM Wasting TWG Jun    2020     9
#>  7 Announcements & Nutritionists needed Marie Lecuyer    Mar    2014     8
#>  8 Announcements & Nutritionists needed Marie Lecuyer    Jul    2014     8
#>  9 Announcements & Nutritionists needed Michael ALVES    Sep    2015     7
#> 10 Announcements & Nutritionists needed Ciara Passmore   Aug    2015     6
#> # … with 2,503 more rows

Counting of topics by year is specified as follows:

get_themes() %>%
  get_themes_topics() %>%
  count_authors(by_date = "year")

which results in:

#> # A tibble: 1,997 x 4
#>    Theme                                  Author                      Year     n
#>    <chr>                                  <chr>                      <dbl> <int>
#>  1 Announcements & Nutritionists needed   Marie Lecuyer               2014    47
#>  2 Announcements & Nutritionists needed   Anonymous 1494              2015    28
#>  3 Announcements & Nutritionists needed   Tamsin Walters              2015    26
#>  4 COVID-19 and nutrition programming     GTAM Wasting TWG            2020    22
#>  5 Announcements & Nutritionists needed   Michael ALVES               2015    18
#>  6 Announcements & Nutritionists needed   Nutrition International -…  2018    18
#>  7 Announcements & Nutritionists needed   Tamsin Walters              2018    17
#>  8 Announcements & Nutritionists needed   Mark Hawkes                 2019    16
#>  9 Announcements & Nutritionists needed   Anonymous 1271              2012    15
#> 10 Infant and young child feeding interv… Alessandro Iellamo          2020    15
#> # … with 1,987 more rows

Counting of topics overall across the years is specified as follows:

get_themes() %>%
  get_themes_topics() %>%
  count_authors(by_date = "all")

which results in:

#> # A tibble: 1,548 x 3
#>    Theme                                Author                              n
#>    <chr>                                <chr>                           <int>
#>  1 Announcements & Nutritionists needed Tamsin Walters                    103
#>  2 Announcements & Nutritionists needed Marie Lecuyer                      61
#>  3 Announcements & Nutritionists needed Michael ALVES                      58
#>  4 Announcements & Nutritionists needed Anonymous 1494                     49
#>  5 Announcements & Nutritionists needed Nutrition International - NTEAM    32
#>  6 Announcements & Nutritionists needed Alan Mason                         29
#>  7 Announcements & Nutritionists needed Regine Kopplow                     26
#>  8 Announcements & Nutritionists needed Mark Hawkes                        23
#>  9 COVID-19 and nutrition programming   GTAM Wasting TWG                   22
#> 10 Assessment and Surveillance          Anonymous 81                       21
#> # … with 1,538 more rows

By default, the output of count_authors arranges the results by descending frequency of counts of each topic raised by an author by the grouping variable. This default behaviour can be changed by setting the .sorted argument to FALSE.

Arranging topics by number of views

Summarising the number of topics or questions raised within the en-net online forum by arranging them based on number of views can proxy level of interest to a specific topic by those participating in the forum. This is facilitated using the arrange_views function. Ranking of topics by number of views is done per thematic area and by a specific time period. Ranking of topics by number of views by thematic area and by month and year is performed by default:

get_themes() %>%
  get_themes_topics() %>%
  arrange_views()

which results in:

#> # A tibble: 3,006 x 9
#>    Theme   Topic          Views Author  Posted     Link      Replies Month  Year
#>    <chr>   <chr>          <int> <chr>   <date>     <chr>       <int> <fct> <dbl>
#>  1 Adoles… Age group of …   599 Anonym… 2020-02-15 https://…       1 Feb    2020
#>  2 Adoles… Launch of res…  1959 Jo Lof… 2018-05-23 https://…       0 May    2018
#>  3 Adoles… Reaching out …  2155 Emily … 2018-06-18 https://…       3 Jun    2018
#>  4 Adoles… adolescent ma…  2120 Anonym… 2018-06-21 https://…       1 Jun    2018
#>  5 Adoles… adolescent ma…  1933 Anonym… 2018-06-21 https://…       1 Jun    2018
#>  6 Adoles… anthropometry…  1890 Emily … 2018-06-29 https://…       2 Jun    2018
#>  7 Adoles… Teen/adolesce…  1827 Anne H… 2018-06-19 https://…       1 Jun    2018
#>  8 Adoles… health educat…  1609 Anonym… 2018-06-19 https://…       1 Jun    2018
#>  9 Adoles… Is there any …   899 Aisha … 2020-06-12 https://…       1 Jun    2020
#> 10 Adoles… Assessing nut…  1912 Ursula… 2018-07-25 https://…       3 Jul    2018
#> # … with 2,996 more rows

Arranging topics by number of views by thematic area and by year is performed as follows:

get_themes() %>%
  get_themes_topics() %>%
  arrange_views(by_date = "year")

which results in:

#> # A tibble: 3,006 x 9
#>    Theme    Topic        Views Author  Posted     Link       Replies Month  Year
#>    <chr>    <chr>        <int> <chr>   <date>     <chr>        <int> <fct> <dbl>
#>  1 Adolesc… Reaching ou…  2155 Emily … 2018-06-18 https://w…       3 Jun    2018
#>  2 Adolesc… adolescent …  2120 Anonym… 2018-06-21 https://w…       1 Jun    2018
#>  3 Adolesc… Launch of r…  1959 Jo Lof… 2018-05-23 https://w…       0 May    2018
#>  4 Adolesc… adolescent …  1933 Anonym… 2018-06-21 https://w…       1 Jun    2018
#>  5 Adolesc… Assessing n…  1912 Ursula… 2018-07-25 https://w…       3 Jul    2018
#>  6 Adolesc… anthropomet…  1890 Emily … 2018-06-29 https://w…       2 Jun    2018
#>  7 Adolesc… Teen/adoles…  1827 Anne H… 2018-06-19 https://w…       1 Jun    2018
#>  8 Adolesc… Adolescent …  1793 Tamsin… 2018-08-01 https://w…       3 Aug    2018
#>  9 Adolesc… adolescent …  1749 Anonym… 2018-07-04 https://w…       1 Jul    2018
#> 10 Adolesc… MUAC tape f…  1693 Anonym… 2018-09-27 https://w…       1 Sep    2018
#> # … with 2,996 more rows

Arranging topics by number of views by thematic area overall across the years is performed as follows:

get_themes() %>%
  get_themes_topics() %>%
  arrange_views(by_date = "all")

which results in:

#> # A tibble: 3,006 x 9
#>    Theme    Topic        Views Author  Posted     Link       Replies Month  Year
#>    <chr>    <chr>        <int> <chr>   <date>     <chr>        <int> <fct> <dbl>
#>  1 Adolesc… Reaching ou…  2155 Emily … 2018-06-18 https://w…       3 Jun    2018
#>  2 Adolesc… adolescent …  2120 Anonym… 2018-06-21 https://w…       1 Jun    2018
#>  3 Adolesc… Launch of r…  1959 Jo Lof… 2018-05-23 https://w…       0 May    2018
#>  4 Adolesc… adolescent …  1933 Anonym… 2018-06-21 https://w…       1 Jun    2018
#>  5 Adolesc… Assessing n…  1912 Ursula… 2018-07-25 https://w…       3 Jul    2018
#>  6 Adolesc… anthropomet…  1890 Emily … 2018-06-29 https://w…       2 Jun    2018
#>  7 Adolesc… Teen/adoles…  1827 Anne H… 2018-06-19 https://w…       1 Jun    2018
#>  8 Adolesc… Adolescent …  1793 Tamsin… 2018-08-01 https://w…       3 Aug    2018
#>  9 Adolesc… adolescent …  1749 Anonym… 2018-07-04 https://w…       1 Jul    2018
#> 10 Adolesc… MUAC tape f…  1693 Anonym… 2018-09-27 https://w…       1 Sep    2018
#> # … with 2,996 more rows

By default, the output of arrange_views is grouped by thematic area. This default behaviour can be changed by setting the by_theme argument to FALSE. For example, to arrange the topics by number of views by month and year across all themes:

get_themes() %>%
  get_themes_topics() %>%
  arrange_views(by_theme = FALSE)

which results in:

#> # A tibble: 3,006 x 9
#>    Theme      Topic         Views Author Posted     Link     Replies Month  Year
#>    <chr>      <chr>         <int> <chr>  <date>     <chr>      <int> <fct> <dbl>
#>  1 Infant an… Breastfeedin…  9174 Anony… 2010-01-07 https:/…       3 Jan    2010
#>  2 Announcem… Nutrition in…  8380 Marie… 2010-01-05 https:/…      NA Jan    2010
#>  3 Assessmen… How to Maint…  5560 Anony… 2010-01-15 https:/…       2 Jan    2010
#>  4 Assessmen… Interpretati…  8497 Tamsi… 2011-01-05 https:/…      10 Jan    2011
#>  5 Assessmen… Calculating …  7503 Ali M… 2011-01-19 https:/…       3 Jan    2011
#>  6 Assessmen… Prospective …  5922 Jeff … 2011-01-27 https:/…       7 Jan    2011
#>  7 Announcem… IYCF Consult…  5350 Aliso… 2011-01-04 https:/…      NA Jan    2011
#>  8 Announcem… Technical Su…  5313 Tamsi… 2011-01-18 https:/…      NA Jan    2011
#>  9 Cross-cut… Transitionin…  5169 Anony… 2011-01-25 https:/…       1 Jan    2011
#> 10 Assessmen… Result with …  5087 Anony… 2011-01-25 https:/…       2 Jan    2011
#> # … with 2,996 more rows

Arranging topics by number of replies

Summarising the number of topics or questions raised within the en-net online forum by arranging them based on number of replies can proxy level of interest to a specific topic by those participating in the forum specifically those who provide responses and feedback to responses within the discussion. This is facilitated using the arrange_replies function. Ranking of topics by number of replies is done per thematic area and by a specific time period. Ranking of topics by number of replies by thematic area and by month and year is performed by default:

get_themes() %>%
  get_themes_topics() %>%
  arrange_replies()

which results in:

#> # A tibble: 1,777 x 9
#>    Theme   Topic          Views Author  Posted     Link      Replies Month  Year
#>    <chr>   <chr>          <int> <chr>   <date>     <chr>       <int> <fct> <dbl>
#>  1 Adoles… Age group of …   599 Anonym… 2020-02-15 https://…       1 Feb    2020
#>  2 Adoles… Launch of res…  1959 Jo Lof… 2018-05-23 https://…       0 May    2018
#>  3 Adoles… Reaching out …  2155 Emily … 2018-06-18 https://…       3 Jun    2018
#>  4 Adoles… anthropometry…  1890 Emily … 2018-06-29 https://…       2 Jun    2018
#>  5 Adoles… adolescent ma…  2120 Anonym… 2018-06-21 https://…       1 Jun    2018
#>  6 Adoles… adolescent ma…  1933 Anonym… 2018-06-21 https://…       1 Jun    2018
#>  7 Adoles… Teen/adolesce…  1827 Anne H… 2018-06-19 https://…       1 Jun    2018
#>  8 Adoles… health educat…  1609 Anonym… 2018-06-19 https://…       1 Jun    2018
#>  9 Adoles… Is there any …   899 Aisha … 2020-06-12 https://…       1 Jun    2020
#> 10 Adoles… Assessing nut…  1912 Ursula… 2018-07-25 https://…       3 Jul    2018
#> # … with 1,767 more rows

Arranging topics by number of replies by thematic area and by year is performed as follows:

get_themes() %>%
  get_themes_topics() %>%
  arrange_replies(by_date = "year")

which results in:

#> # A tibble: 1,777 x 9
#>    Theme    Topic        Views Author  Posted     Link       Replies Month  Year
#>    <chr>    <chr>        <int> <chr>   <date>     <chr>        <int> <fct> <dbl>
#>  1 Adolesc… Adolescent …  1793 Tamsin… 2018-08-01 https://w…       3 Aug    2018
#>  2 Adolesc… Assessing n…  1912 Ursula… 2018-07-25 https://w…       3 Jul    2018
#>  3 Adolesc… Reaching ou…  2155 Emily … 2018-06-18 https://w…       3 Jun    2018
#>  4 Adolesc… anthropomet…  1890 Emily … 2018-06-29 https://w…       2 Jun    2018
#>  5 Adolesc… MUAC tape f…  1693 Anonym… 2018-09-27 https://w…       1 Sep    2018
#>  6 Adolesc… adolescent …  1749 Anonym… 2018-07-04 https://w…       1 Jul    2018
#>  7 Adolesc… adolescent …  2120 Anonym… 2018-06-21 https://w…       1 Jun    2018
#>  8 Adolesc… adolescent …  1933 Anonym… 2018-06-21 https://w…       1 Jun    2018
#>  9 Adolesc… Teen/adoles…  1827 Anne H… 2018-06-19 https://w…       1 Jun    2018
#> 10 Adolesc… health educ…  1609 Anonym… 2018-06-19 https://w…       1 Jun    2018
#> # … with 1,767 more rows

Arranging topics by number of replies by thematic area overall across the years is performed as follows:

get_themes() %>%
  get_themes_topics() %>%
  arrange_replies(by_date = "all")

which results in:

#> # A tibble: 1,777 x 9
#>    Theme   Topic          Views Author  Posted     Link      Replies Month  Year
#>    <chr>   <chr>          <int> <chr>   <date>     <chr>       <int> <fct> <dbl>
#>  1 Adoles… Adolescent sc…  1793 Tamsin… 2018-08-01 https://…       3 Aug    2018
#>  2 Adoles… Assessing nut…  1912 Ursula… 2018-07-25 https://…       3 Jul    2018
#>  3 Adoles… Reaching out …  2155 Emily … 2018-06-18 https://…       3 Jun    2018
#>  4 Adoles… anthropometry…  1890 Emily … 2018-06-29 https://…       2 Jun    2018
#>  5 Adoles… Is there any …   899 Aisha … 2020-06-12 https://…       1 Jun    2020
#>  6 Adoles… Age group of …   599 Anonym… 2020-02-15 https://…       1 Feb    2020
#>  7 Adoles… MUAC tape for…  1693 Anonym… 2018-09-27 https://…       1 Sep    2018
#>  8 Adoles… adolescent sc…  1749 Anonym… 2018-07-04 https://…       1 Jul    2018
#>  9 Adoles… adolescent ma…  2120 Anonym… 2018-06-21 https://…       1 Jun    2018
#> 10 Adoles… adolescent ma…  1933 Anonym… 2018-06-21 https://…       1 Jun    2018
#> # … with 1,767 more rows

By default, the output of arrange_replies is grouped by thematic area. This default behaviour can be changed by setting the by_theme argument to FALSE. For example, to arrange the topics by number of replies by month and year across all themes:

get_themes() %>%
  get_themes_topics() %>%
  arrange_replies(by_theme = FALSE)

which results in:

#> # A tibble: 1,777 x 9
#>    Theme     Topic         Views Author  Posted     Link     Replies Month  Year
#>    <chr>     <chr>         <int> <chr>   <date>     <chr>      <int> <fct> <dbl>
#>  1 Infant a… Breastfeedin…  9174 Anonym… 2010-01-07 https:/…       3 Jan    2010
#>  2 Assessme… How to Maint…  5560 Anonym… 2010-01-15 https:/…       2 Jan    2010
#>  3 Assessme… Interpretati…  8497 Tamsin… 2011-01-05 https:/…      10 Jan    2011
#>  4 Assessme… Prospective …  5922 Jeff M… 2011-01-27 https:/…       7 Jan    2011
#>  5 Assessme… Calculating …  7503 Ali Ma… 2011-01-19 https:/…       3 Jan    2011
#>  6 Assessme… Result with …  5087 Anonym… 2011-01-25 https:/…       2 Jan    2011
#>  7 Cross-cu… Transitionin…  5169 Anonym… 2011-01-25 https:/…       1 Jan    2011
#>  8 Assessme… Nutritional …  7560 Mary M… 2012-01-01 https:/…      10 Jan    2012
#>  9 Upcoming… Regional SMA…  5703 Yara S… 2012-01-10 https:/…       8 Jan    2012
#> 10 Micronut… multi-micron…  6032 REBECC… 2012-01-18 https:/…       6 Jan    2012
#> # … with 1,767 more rows