ennet
package provides a set of functions that extracts
information from the en-net online forum.
This set of functions was built on top of the rvest
package which
provides robust and performant web scraping functions and the dplyr
package which
provides a full suite of data manipulation functions. The
ennet
package was designed to be able to interact with how
the en-net online forum has been structured.
The en-net online forum website has a very clear and clean structure. The opening page is a list of thematic areas which are linked to each of their respective webpages. In each of these thematic area webpages is another list, this time a list of topics raised within the thematic area. These topics are the text that an online user provides as the title for the question she/he is going to ask. Each of the topics are then again linked to their respective webpages that show the actual full question raised and the ensuing responses and discussion stemming from that question.
The en-net online forum structure can be summarised graphically as follows:
Based on this structure, the following functions are available with
ennet
package for extracting text data:
get_themes
- function to get a list of thematic
areas in the forum;
get_theme_topics
and get_themes_topics
- functions to get list of topics for a specific thematic area or
thematic areas; and,
get_topic_discussions
and
get_topics_discussions
- functions to get list of
discussions for a specific topic or topics,
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
:
count_topics
- function to count the number of
topics or questions by theme and date;
count_authors
- function to count the number of
topics attributed to a specific author;
arrange_views
- function to arrange topics by number
of views; and,
arrange_replies
- function to arrange topics by
number of replies.
In addition to these two sets of key functions, en-net
package also includes a function - update_topics
- that
extracts the en-net
online forum dataset and updates it at a given time interval. This
is a convenience wrapper function to get_themes_topics
that
is potentially useful for those who wants to build dashboards or
applications that uses data from the en-net online
forum.
Two datasets are also included in the en-net
package.
The first dataset is a data.frame of en-net online forum
themes and the second dataset is a data.frame of en-net online forum
topics.
The en-net
online forum is a rich resource for understanding the community of users
that participate in it. And given how an online forum is designed, that
resource can be tapped relatively easily given that the documentation of
the interaction and discussion between its users happens in real-time.
The ennet
package facilitates the access to that
information through the statistical analysis tool R with which further levels of
analysis can be applied to generate meaningful and valuable
understanding of this specific community and to some extent the greater
nutrition sector at large.
Following are a few practical and meaningful applications of the information generated by the en-net online forum.
The data from the en-net online forum can be used to assess effectiveness of the forum. Effectiveness can be defined as whether the forum has been able to achieve its stated aims/objectives when it was started. Effectiveness can also be expressed in terms of indicators or metrics that reflect overarching principles, ideals or values that those who started the forum adhere to or that the community of users and the wider sector or society believe in. These may include values of inclusion, participation, scientific rigour among others. Given that the forum has been in existence for many years now, information is available over the same period allowing for assessing temporal variation in effectiveness (as defined). This application is a more normative approach and will involve creating or developing metrics or taking relevant metrics from other sectors and applying those to this case.
Given the nature of the en-net online forum as a quick point of recourse for field practitioners to seek answers to practical questions and challenges faced, it can be expected that the data from the forum contains information on what these topics are. These information can then be used to identify most common or most important information, knowledge and skills that have been asked about. By identifying these gaps in information, knowledge and/or skills and by understanding the evolution of these needs over time, we can potentially predict training needs in the near term and over time. This application is a more formative approach in that we let the data tell us what information it holds.