calculate_score_topic: Calculate scores of a self-chosen topic
In JulFriedrich/miRetrieve: miRNA Text Mining in Abstracts

Description Usage Arguments Details Value See Also

Calculate score of a self-chosen topic for each abstract to identify abstracts possibly corresponding to the topic of interest.

calculate_score_topic(
  df,
  keywords,
  case = FALSE,
  col.score = "topic_score",
  col.indicate = NULL,
  threshold = NULL,
  discard = FALSE,
  col.abstract = Abstract
)

`df`	Data frame containing abstracts.
`keywords`	Character vector. Vector containing keywords. The score is calculated based on these keywords. How much weight a keyword in `keywords` carries is determined by how often it is present in `keywords`, e.g. if a keyword is mentioned twice in `keywords` and it is mentioned only once in an abstract, it adds 2 points to the score.
`case`	Boolean. If `case = TRUE`, terms contained in `keywords` are case sensitive. If `case = FALSE`, terms contained in `keywords` are case insensitive.
`col.score`	String. Name of `topic_score` column.
`col.indicate`	String. Optional. Name of indicating column. If a string is provided, an extra column is added to `df`, indicating if the abstract corresponds to the topic of interest by "Yes" or "No".
`threshold`	Integer. Optional. Threshold to decide if abstract corresponds to topic of interest. If `col.topic` is specified or `discard = TRUE` without `threshold` being specified, `threshold` is automatically set to `1`.
`discard`	Boolean. If `discard = TRUE`, only abstracts are kept that correspond to the topic of interest.
`col.abstract`	Symbol. Column containing abstracts.

Calculate score of a self-chosen topic for each abstract to identify abstracts possibly corresponding to the topic of interest. This score is added to the data frame as an additional column, usually called topic_score, containing the calculated topic score. If there is more than one topic of interest, the column topic_score should be appropriately renamed. To decide which abstracts are considered to correspond to the topic of interest, a threshold can be set via the threshold argument. Furthermore, an additional column can be added, verbally indicating if the abstract corresponds to the topic. Choosing the right threshold can be facilitated using plot_score_topic().

Data frame with calculated topic scores. If discard = FALSE, adds extra columns to the original data frame with the calculated topic scores. If discard = TRUE, only abstracts corresponding to the topic of interest are kept.

assign_topic(), plot_score_topic()

Other score functions: assign_topic(), calculate_score_animals(), calculate_score_biomarker(), calculate_score_patients(), plot_score_animals(), plot_score_biomarker(), plot_score_patients(), plot_score_topic()