Assign topics based on precalculated scores

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
)

Arguments

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.

Value

Data frame with topics based on precalculated topic scores.

Details

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".

See also

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()