syuzhet | An R package for the extraction of sentiment and sentiment-based plot arcs from text | Predictive Analytics library
kandi X-RAY | syuzhet Summary
kandi X-RAY | syuzhet Summary
An R package for the extraction of sentiment and sentiment-based plot arcs from text. The name "Syuzhet" comes from the Russian Formalists Victor Shklovsky and Vladimir Propp who divided narrative into two components, the "fabula" and the "syuzhet." Syuzhet refers to the "device" or technique of a narrative whereas fabula is the chronological order of events. Syuzhet, therefore, is concerned with the manner in which the elements of the story (fabula) are organized (syuzhet). The Syuzhet package attempts to reveal the latent structure of narrative by means of sentiment analysis. Instead of detecting shifts in the topic or subject matter of the narrative (as Ben Schmidt has done), the Syuzhet package reveals the emotional shifts that serve as proxies for the narrative movement between conflict and conflict resolution. This was an idea inspired by the late Kurt Vonnegut in an essay titled "Here's a Lesson in Creative Writing" in his collection A Man Without A Country ( Random House, 2007). A lecture Vonnegut gave on this subject is available via youTube.
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QUESTION
I am trying to use the mixed_messages function from the syuzhet package.
How do I apply this to every row in my data frame?
...ANSWER
Answered 2021-Jul-12 at 20:09You can use the apply function.
QUESTION
I am attempting to obtain sentiment scores on comments in a data frame with two columns, Author and Comment. I used the command
...ANSWER
Answered 2021-Apr-23 at 13:21Welcome to SO, Père Noël.
Pacakge {sentimenter}'s get_sentences() breaks the text input into sentences by default, as its name implies. To reconstruct the original text input as the defining key in your final data frame, you need to group and summarize the sentence-based output produced by sentiment().
In this example, I will simply average the sentiment scores, and append sentences by their element_id.
QUESTION
I'm doing some very basic sentiment analysis on a pretty large set of data that continues to grow every day. I need to feed this data into a shiny app where I can adjust the date range. Rather than running the analysis over and over again, what I'd like to do is create a new CSV with the sum of each sentiment score by date. I'm having trouble iterating over the date though. Here's some sample data and the lapply() statement I tried that is not working.
ANSWER
Answered 2021-Jan-18 at 23:55Function lapply iterates over elements of a list. Data frame is technically a list with each column as an element of that list. So in your example you are iterating over columns rather than rows, or even dates (that seems to be your goal). Instead of lapply I'd use dplyr::group_by in combination with one of: dplyr::do, dplyr::summarize or tidyr::nest. See documentations for each function to figure out which function suits the most your need.
QUESTION
tl,dr: My function seems to work, but then I lapply it and it doesn't. Is it the function or the lapplying?
The dataI have a datatable that contains text which is already tokenised into a character vector:
...ANSWER
Answered 2020-Dec-06 at 15:49Edit: this should get you want you want.
QUESTION
I'm trying to create a key-value store with the key being entities and the value being the average sentiment score of the entity in news articles.
I have a dataframe containing news articles and a list of entities called organizations1 identified in those news articles by a classifier. The first row of the organization1 list contains the entities identified in the article on the first row of the news_us dataframe. I'm trying to iterate through the organization list and creating a key-value store with the key being the entity name in the organization1 list and the value being the sentiment score of the news description in which the entity was mentioned.
I can get the sentiment scores for the entity from an article but I wanted to add them together and average the sentiment score.
...ANSWER
Answered 2020-May-04 at 18:27Your problem seems to arise from the use of 'unlist'. Avoid this, as it drops the NULL values and concatenates list entries with multiple values.
Your organization1 list has 7 entries (two of which are NULL and one is length = 2). You should have 6 entries if this is to match the news_us data.frame - so something is out of sync there.
Let's assume the first 6 entries in organization1 are correct; I would bind them to your data.frame to avoid further 'sync errors':
news_us$organization1 = organization1[1:6]
Then you need to do the sentiment analysis on each row of the data.frame and bind the results to the organization1 value/s. The code below might not be the most elegant way to achieve this, but I think it does what you are looking for:
QUESTION
I'm trying to create a key value store with the key being entities and the value being the average sentiment score of the entity in news articles.
I have a dataframe containing news articles and a list of entities called organizations1 indentified in those news articles by a classifier. The first rows of the organization1 list contains the entities identified in the article on the first row of the news_us dataframe. I'm trying to iterate through the organizations list and creating a key value store with the key being the entity in the organization1 list and the value being the sentiment score of the news description in which the entity was mentioned. The code I have doesn't change the scores in the sentiment list and I don't know why. My first guess was that I would have to use the $ operator on the sentiment list to add the value but that didn't change anything either. Here is the code I have so far:
...ANSWER
Answered 2020-May-04 at 05:56I am not sure how organization1 and news_us$description are related but perhaps, you meant to use it something like this?
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