assign_topic: Assign topics based on precalculated scores
In JulFriedrich/miRetrieve: miRNA Text Mining in Abstracts

Description Usage Arguments Details Value See Also

Assign topics to abstracts based on precalculated scores.

assign_topic(
  df,
  col.topic,
  threshold,
  topic.names = NULL,
  col.topic.name = "Topic",
  col.pmid = "PMID",
  discard = FALSE
)

`df`	Data frame containing precalculated topic scores and PubMed-IDs.
`col.topic`	Character vector. Vector with column names containing precalculated topic scores.
`threshold`	Integer vector. Vector containing thresholds for topic columns. Positions in `threshold` correspond to positions in `col.topic`.
`topic.names`	Character vector. Optional. Vector containing names of new topics. Positions in `topic.names` correspond to positions in `col.topic`. If `topic.names` is not provided, `col.topic` is used to name the new topics.
`col.topic.name`	String. Name of the new topic column.
`col.pmid`	String. Column containing PubMed-IDs.
`discard`	Boolean. If `discard = TRUE`, only abstracts with a newly assigned topic are kept. Abstracts without a newly assigned topic are discarded.

Assign topics to abstracts based on precalculated scores. assign_topic() compares different precalculated topic scores and assigns the abstract to the topic with the highest score. If there is a tie between topic scores, the abstract is assigned to all topics in question. If an abstract matches no topic, it is assigned to the topic "Unknown".

Data frame with topics based on precalculated topic scores.

calculate_score_topic(), plot_score_topic(), add_col_topic()

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