Dear Bharatendra Rai sir you are doing great job with these videos, very informational. Please guide how to get data from twitter or other social media handles for a specific word. For example real estate market's particular project in Chennai. Thanks for your valuable inputs.
@@bkrai thanks i will try and get back to you my question is if i want to know what are kolkata people tweeting on one specific tweet how may i drill down to location and then to that #subject
It was a Great Lecture and very easy to understand. Thanks for this video. Can you please tell me how did you pull tweets after earnings. which part of the video or lines we need to follow to pull the tweets? I have followed this complete video and got the results. I want to extract Preprocessed csv file..please help me by your suggestions? Is this preprocessed file stored in R library of my computer?
Thanks Bharatendra sir for sharing your knowledge.IT has been very helpful in my current project. We have below list of sentiments packages. #syuzhet #SentimentR #Rsentiment #Sentimentanalysis I am still validating all of above. Please let us know your thought about package recommendation for sentiment analysis.
Thanks sir for your confirmation. yes Syuzhet is giving expected result for emotion and sentiments with some misclassification. I am using SentimentR to get avg sentiment by respective dimension and to get positive word list and negative word list.
Thanks so much for this detailed explanation. Please I'm having an issue fixing the TermDocumentMatrix error. I get this error when I get to the tdm: Error in nchar(Terms(x), type = "chars") : invalid multibyte string, element 220 How do I fix it?
What version of R have u used for the entire project as I have having difficulties with R 3.5 and R 4.0 for installing some packages like Corpus and iconv
This video is really helpful, thank you very much! but how can we evaluate the performance of the sentiment analysis you have just made? Are there any metric to use? Please help...
One way could be to score tweets manually and then compare the results from automated sentiment analysis. And then mismatch % could work as a metric to assess the performance.
Could you please help me out... I was unable to get the letter cloud. All steps followed as mentioned in the video. The video was very helpful in all the other aspects.
Many thanks for your video. Can you please tell us something more about the Datasets Apple & Apple 2. Did you export it from Twitter Analytics/Activity.
Fantastic video! Surprised I have not run into your channel before. I am analyzing customer survey results from different countries, and one problem that I am having is that some of the countries have very polite people (not a bad thing of course) and their survey results show positive, when in fact they are not happy with the result. Have you had this problem before, and if so how did you handle it?
For the Sentiment bar chart comparison, It would be an easier comparison if the bars were based on % of total row count instead of comparing counts. Would you do rowsum(x) / sum(x)? Or is it colsum(x) / sum(x)
For converting y-axis to % you can use: barplot(100*colSums(s)/sum(s), las = 2, col = rainbow(10), ylab = 'Percentage', main = '% Sentiment Scores for Apple Tweets')
Mr.Baharat, After getting text (tweets) and clean them, How can we rewrite them as a .csv file to get the sentiment analysis of the new data with the clean text. What you did here is that you analysed the raw data with unclean text? Thanks
If you allow me, I would like to ask another question. The barplot with the Sentiment Scores at the end of your tutorial is very nice. My question is whether there is a way to view the IDs of all the tweets which contain words which have been classified under, say, Anger.
hello sir, i have a doubt, for the first file apple.csv you have done all the pre processing(cleaning of data) ,but for the second time when you are performing the actual sentimental analysis you have not done any pre processing. So you are doing the sentimental analysis without any cleaning in the second file?
Pre processing helps when you are developing wordcloud as you don't want to see thing that are not relevant. However, for sentiment analysis it may not matter if common words like 'the' or 'is' are there or not.
Excellent video Sir. Just wanted to know - like you have changed stocks to stock, is there a standard method to convert each word to its root form? Similar to lemmatization in Python
Great explanation, sir. How can I do the same but for plain text (e.g., comments withdrawn directly from tripadvisor)? And how can I use sentimentr instead? Thank you so much for you wonderful explanation.
Hey bharat, Thank you very much for such a nice explanation. Need your help. am not able to see the output of letter cloud as shown. Please suggest. Regards, Murali
Thank you for your reply. Actually, am using the same code for lettercloud but the output is not same as yours. code: "letterCloud(w,word = "apple",wordSize = 1)" The output is apple with black letters. Please share your email id so that I can share the output
Thank you for this very nice tutorial on Sentiment Analysis. You mentioned that all the tweets were in a csv file and the column of interest was the first column. I would like to know if there was a cleaning of the tweets before using the csv file for analysis in R. My point is that if there are commas being used in some tweets, that would distort the CSV file. I guess those commas are removed before creating the CSV file. Can you please confirm this point?
Really excellent video!! Where can we find dictionaries with keywords annotated with sentiments (e.g. ugly as you mentioned in video)? Also, how can we add sentiment dictionary for new language? Any video on these topics? Thank you very much ... :)
May i know why you created Corpus? As you mentioned that corpus is a collection of documents, so why you want each tweet to be treated as a document? What is the goal behind that?
Awesome video. I see the video was uploaded around 1 year back. Is there any new library after that which can further simplify the coding ? Also will there be further simplification of the code if we use Microsoft Cognitive Services (Text Analytics API) .
If you are doing sentiment analysis, the code has just one or two lines. When using other tools such as MS cognitive services, note that the results are likely to be different.
hello sir thanks for such a knowledgeable video sir I want to know that which year of data you used in this video and may we use this data for research purposes.please reply thanks again.
what should users of window use in the place of utf-8-mac at 1:50? I have tried to reproduce your example but it is not working, sorry I am newbie to these things, thank you in advance!
Hi Bharat; When looking at the data file, we can see that most of columns are N/A. How we can get Longitude and Latitude for example? what is the meaning of replyToSN and replyToSID? you have mentioned that Apple two datasets are taken from Twitter before and after quarterly earnings report. Could you please let us know what quarter is that? I mean is it after the 1, 2, 3 or fourth quarter the data was taken???
Longitude and Latitude is only available for those Twitter users who agree to share their location. Due to privacy reasons many people do not like to share their location and that's why majority of tweets do not have this info. replyToSN - reply to Screenname replyToSID - reply to sender ID apple2.csv has data for 2nd quarter of 2017.
hi, your video is good and very useful for me. can you please provide how to get file from twitter and iam new to work on R software. if you don't mind i need some basic videos step by step process from getting data and doing wordcloud and sentiment analysis on R. i am waiting for your reply for example i need a data from twitter big data in agriculture. like that i want to get data sheet from twitter and run the word cloud and sentiment analysis on R. can you suggest me
Let's say your twitter data is in apple. Let's say you have all sentiment scores in SCORES. Then you can combine them using cbind(apple, SCORES). It will combine the columns.
Thank you sir for simple tutorial on sentiment analysis.it is really helpful for me. sir kindly share the link from where i can download this apple.csv file to continue my work in R I need your help sir
Mr.Bharat, when i want now to pull new data about apple from Twitter , R returns the tweets dated 2018. My question is: how can i pull tweets ,for example, about the second quarter 2016? Is there any way to specify an exact date range to pull tweets? Regards.
Hi! I have a question While trying to plot the wordcloud I get this message: hertha could not be fit on page. It will not be plotted. 6: In wordcloud(words = names(w), freq = w, max.words = 100, min.freq = 5, : Any way I can fix it?
Hello Sir, I have imported all the mentioned libraries, but when I run the command: get_nrc_sentiment, I am getting the error as: Error: 'vec_as_subscript' is not an exported object from 'namespace:vctrs' Run `rlang::last_error()` to see where the error occurred. Can you please help
Hey, i super appreciate to your work it easy to understand, but i have questions is that code can be implemented on any language such as Bahasa Indonesia? Thanks you, if you are available for reply
thank you very much for this helpful tutorial. But is it possible to display this plot on a shiny app as an image? Can I store this plot in a variable and display it on a shiny app.
Sir, unable to perform sentiment analysis due to unavailability of package syuzhet and lubridate.... others like ggplot,scales are there... R is showing error displaying there is no packages named syuzhet and lubridate... what to do Sir.. plz help..
sir i am having problem in sentiment analysis! when i try to run the statement get_nrc_sentiment(tweets) it is showing error in .dataframe and error states undefined colums selected. and when i try to run head (s) it shows object not found. please let me know asap. thanks
It may happen if data size is to big to be handled by your computer. Try reducing data size. Or you can try google colab: ua-cam.com/video/XVfn6IpoUPU/v-deo.html
Hi! Thanks a lot for your video! I have a question. How do I remove stopwords for German? Is it the same line of code with putting german instead of english? Thanks
I am getting the below waring messages, how can I ignore this Warning message: In tm_map.SimpleCorpus(corpus, tolower) : transformation drops documents
Sir, i ran Library (tm) also on window but getting Error in iconv(apple$text, to = "utf-win") : unsupported conversion from '' to 'utf-win' in codepage 1252. pl help me .
Too good Video....your explanation is awesome sir....Thank you so much
You are welcome!
By far one of the best teacher of Data Science, who believes in keeping it simple. Absolutely love them.
Thanks for comments!
Thank you, Prof Rai. I searched many tutorials for the sentiment analysis on Tweets on UA-cam, and your tutorial was the best one.
You're very welcome!
Whichever topic I take to study in R software, I will find your video teaching most interestingly and easily, thank you so much, sir
You are most welcome!
The best explanation and walk-through of sentiment analysis I've seen so far. Well done, very helpful.
Thanks for the feedback!
Dear Bharatendra Rai sir you are doing great job with these videos, very informational. Please guide how to get data from twitter or other social media handles for a specific word. For example real estate market's particular project in Chennai.
Thanks for your valuable inputs.
you can use a word or phrase, just as we use when we do google search.
@@bkrai thanks i will try and get back to you
my question is if i want to know what are kolkata people tweeting on one specific tweet how may i drill down to location and then to that #subject
@@bkrai thanks
You have explained everything very clearly and it is very helpful for beginners like me. Thank You
Thanks for comments!
Sir I have one doubt. Why have you used : to = "utf-8-mac" in line no.7.
Is it same everytime in all the problems?
@@amanakshansh1021 no, you can just write utf8 instead.
Excellent one Sir.... Please keep sharing such videos ....Your way of explaining things is Awesome...
Thanks for comments and feedback!
Very well explained Bharatendra. I am learning lots of interesting things in R from you.
Thanks for comments!
Absolutely awesome video. Leart from your video more than my expectation. Clear and sensational! Thank you.
Thanks for comments!
Excellent description on sentiment analysis, very useful !!!
Thanks for comments!
Excellent. Very well explained. Thanks a lot, Dr.
Most welcome!
Thank you sir for a simple tutorial on sentiment analysis and word cloud. Quite helpful for my marketing research class.
Regards.
Thanks for comments!
Dear Bharatendra ..awesome video thanks for efforts to share knowledge . superb
Thanks for comments!
Can you please help, after doing text preprocessing I am trying to perform tdm however getting bellow error.
dtm
Nothing to say: pure quality
Thanks!
you are simply great. i tried and it worked really well. Thank you so much for clear explanation
Thanks for your comments!
Very good explanation! greetings from Perú
!Thanks and welcome
It was a Great Lecture and very easy to understand. Thanks for this video.
Can you please tell me how did you pull tweets after earnings.
which part of the video or lines we need to follow to pull the tweets?
I have followed this complete video and got the results. I want to extract Preprocessed csv file..please help me by your suggestions?
Is this preprocessed file stored in R library of my computer?
For pulling tweets you can follow 1st video in this playlist:
ua-cam.com/play/PL34t5iLfZddt0tt5GdDy3ny6X5RQvwrp6.html
very good presentation , with simple logics & low code implementation method.
Thanks a lot!
This is simply awesome and so much interesting. Loved it. Thank you so much Sir.
Thanks!
Thanks Bharatendra sir for sharing your knowledge.IT has been very helpful in my current project. We have below list of sentiments packages.
#syuzhet
#SentimentR
#Rsentiment
#Sentimentanalysis
I am still validating all of above. Please let us know your thought about package recommendation for sentiment analysis.
syuzhet should work fine for sentiment analysis.
Thanks sir for your confirmation. yes Syuzhet is giving expected result for emotion and sentiments with some misclassification. I am using SentimentR to get avg sentiment by respective dimension and to get positive word list and negative word list.
Thaks Bharatendra, your videos are great full. Do you know how a I coud be specify another idiom (like Spanish) for the sentiment analysis?
Awesome tutorial for sentiment analysis and word cloud!!!!!!! Thank you.
Thanks!
this is an amazing tutorial, thank you Dr.!
You're very welcome!
thank you sir! amazing video. You explanation and pace of videos are on point!. thanks again.
Thanks for comments!
Thank you for your video! It is very helpful and your explanation is so clear! Thanks again.
Thanks for comments!
Thank you soo much for the video but I just wanted to know which algorithm is being used here
For which output?
for apple.csv
Thanks for your clear explanation, learned a lot from your video.
You are welcome!
Thanks so much for this detailed explanation. Please I'm having an issue fixing the TermDocumentMatrix error. I get this error when I get to the tdm:
Error in nchar(Terms(x), type = "chars") :
invalid multibyte string, element 220
How do I fix it?
Difficult to say much without looking at the code.
Awesome videos, examples were very simple and nice, useful materials
Thanks for comments!
What version of R have u used for the entire project as I have having difficulties with R 3.5 and R 4.0 for installing some packages like Corpus and iconv
Probably it has more to do with the computer. I used Mac and that's why used "utf-8-mac". If you are using windows, make sure to use "utf-8".
This video is really helpful, thank you very much! but how can we evaluate the performance of the sentiment analysis you have just made? Are there any metric to use? Please help...
One way could be to score tweets manually and then compare the results from automated sentiment analysis. And then mismatch % could work as a metric to assess the performance.
Thank you very much.
You're a legend! thank you for this video.
You're welcome!
Great video and explanation, very helpful. Thank you.
You are welcome!
Very Helpful...Can you please tell me the interpretation of the sentiment scores...For e.g the Positive Bar crosses the 300 count what does it imply?
Amazingly explained sir. Thanks a lot.
You are welcome!
Could you please help me out...
I was unable to get the letter cloud.
All steps followed as mentioned in the video.
The video was very helpful in all the other aspects.
I too noticed that lettercloud is no more functional. I hope they update the package soon.
Wow!
I didn't expect such quick response..
Thank you so much for the clarification..🙏🏾
You are welcome!
Many thanks for your video. Can you please tell us something more about the Datasets Apple & Apple 2. Did you export it from Twitter Analytics/Activity.
I used this:
ua-cam.com/video/QETCjkQ3CBw/v-deo.html
Thank you for uploading this video. It is very helpful!
Welcome!
Fantastic video! Surprised I have not run into your channel before. I am analyzing customer survey results from different countries, and one problem that I am having is that some of the countries have very polite people (not a bad thing of course) and their survey results show positive, when in fact they are not happy with the result. Have you had this problem before, and if so how did you handle it?
I've not come across this, but seems an interesting problem.
Thankyou for the video.....How do you create apple.csv file in your desktop that contains 1000 tweets?
I got it from Twitter:
ua-cam.com/video/QETCjkQ3CBw/v-deo.html
@@bkrai Thank you sir
You are welcome!
For the Sentiment bar chart comparison, It would be an easier comparison if the bars were based on % of total row count instead of comparing counts.
Would you do rowsum(x) / sum(x)?
Or is it colsum(x) / sum(x)
For converting y-axis to % you can use:
barplot(100*colSums(s)/sum(s),
las = 2,
col = rainbow(10),
ylab = 'Percentage',
main = '% Sentiment Scores for Apple Tweets')
Mr.Baharat, After getting text (tweets) and clean them, How can we rewrite them as a .csv file to get the sentiment analysis of the new data with the clean text. What you did here is that you analysed the raw data with unclean text? Thanks
I wonder the same
This was really helpful, but i was wondering how to do normalization of words, here you did only for one word, what if i need to do for many words?
For 'normalization', which line of the code in the video are you referring to?
Very informative, thanks a lot. Subscribed the moment after watching this video.
Thanks and welcome!
Very good explanation! Excellent job! Btw I have a question about word cloud: does the position of the words mean any relationship?
Position of words is random.
It is really amazing . Can we know how to get those two files from Twitter ? Is there an R package that enable us to do so? Or how? Thanks.
You can get Twitter data using steps in this link:
ua-cam.com/video/QETCjkQ3CBw/v-deo.html
Honestly while you are typing this reply , am really watching the link you provided me .. much appreciated Bharat. Thanks.
Thank you Dr. Rai, very informative video kind sir
You are welcome!
If you allow me, I would like to ask another question. The barplot with the Sentiment Scores at the end of your tutorial is very nice. My question is whether there is a way to view the IDs of all the tweets which contain words which have been classified under, say, Anger.
Yes info regarding ID and screen name is available in the csv file that is downloaded from Twitter.
@@bkrai I understand that. My point was whether it is possible to get that list directly from R by using R codes.
hello sir, i have a doubt, for the first file apple.csv you have done all the pre processing(cleaning of data) ,but for the second time when you are performing the actual sentimental analysis you have not done any pre processing. So you are doing the sentimental analysis without any cleaning in the second file?
Pre processing helps when you are developing wordcloud as you don't want to see thing that are not relevant. However, for sentiment analysis it may not matter if common words like 'the' or 'is' are there or not.
Sr can u plz tell that how to get the accuracy, precision, recall and f-score values for Twitter sentiment analysis using R?
Excellent Video sir, very elaborate. a quick question.. what would be the windows equivalent of the line tweets
tweets
@@bkrai sir this is showing that unsupported conversion from ' ' to 'utf-8' in codepage 65001 , plz help with this
Excellent video Sir. Just wanted to know - like you have changed stocks to stock, is there a standard method to convert each word to its root form? Similar to lemmatization in Python
Awesome video.. thank you for the great explanation!
Thanks for comments!
Hello sir,
What does 'utc-8-mac' mean and what does it do? Could you please explain?
Thank You!
See it now, probably you already figured it out.
Great explanation, sir.
How can I do the same but for plain text (e.g., comments withdrawn directly from tripadvisor)?
And how can I use sentimentr instead?
Thank you so much for you wonderful explanation.
Same process should work fine. Just as in this example there were several tweets, I'm guessing you have several comments from tripadvisor.
Hey bharat, Thank you very much for such a nice explanation.
Need your help.
am not able to see the output of letter cloud as shown.
Please suggest.
Regards,
Murali
Difficult to much without looking at codes. Probably size may be too big and doesn't fit in the area available.
Thank you for your reply.
Actually, am using the same code for lettercloud but the output is not same as yours.
code: "letterCloud(w,word = "apple",wordSize = 1)"
The output is apple with black letters.
Please share your email id so that I can share the output
Hello Professor, first of all, thank you for sharing. I have a question about how to handle a corpus in TXT format.
Thank you for this very nice tutorial on Sentiment Analysis. You mentioned that all the tweets were in a csv file and the column of interest was the first column. I would like to know if there was a cleaning of the tweets before using the csv file for analysis in R. My point is that if there are commas being used in some tweets, that would distort the CSV file. I guess those commas are removed before creating the CSV file. Can you please confirm this point?
CSV file is downloaded from Twitter and the same file is used here.
@@bkrai thanks for your reply.
Hello Sir, the tutorial is nice..I have a question though.. How do you include neutral sentiment?
you can add following line of code after line 88 where scores are stored in 's':
s$neutral
Really excellent video!!
Where can we find dictionaries with keywords annotated with sentiments (e.g. ugly as you mentioned in video)?
Also, how can we add sentiment dictionary for new language? Any video on these topics?
Thank you very much ... :)
May i know why you created Corpus? As you mentioned that corpus is a collection of documents, so why you want each tweet to be treated as a document? What is the goal behind that?
This is a standard way to deal with text data and for analyzing tweets.
Thanks a lot
Sir, What is the Algorithm used here?
It uses nrc lexicon.
Thank you, I have one question how do you extract data from tweeters as you said we have a dataset with apple name, how you made this dataset?
This link has steps:
ua-cam.com/video/QETCjkQ3CBw/v-deo.html
Awesome video. I see the video was uploaded around 1 year back. Is there any new library after that which can further simplify the coding ? Also will there be further simplification of the code if we use Microsoft Cognitive Services (Text Analytics API) .
If you are doing sentiment analysis, the code has just one or two lines. When using other tools such as MS cognitive services, note that the results are likely to be different.
Hello,
Is it possible to use the above method for sentimental analysis of tweets in languages other than english?
I've added it to my list.
Many Thans Rai but please explain me how "iconv" function works in simple words.
I didnt understand that function. and Great Work!
It's needed to convert text data to the right format needed when working on a Mac.
what about windows...?
i have a query, can we do theme tagging for social media data or consumer data ?
hello sir thanks for such a knowledgeable video sir I want to know that which year of data you used in this video and may we use this data for research purposes.please reply thanks again.
It's 2017.
Sir, whats the point of doing all the pre-processing of the tweets if in the end we are using the direct tweets for sentiment analysis?
That's important for visualization. But for sentiment analysis unimportant words are automatically ignored.
what should users of window use in the place of utf-8-mac at 1:50? I have tried to reproduce your example but it is not working, sorry I am newbie to these things, thank you in advance!
for windows use utf-8
@@bkrai thanks a lot for prompt feedback!
Hi Bharat; When looking at the data file, we can see that most of columns are N/A. How we can get Longitude and Latitude for example? what is the meaning of replyToSN and replyToSID?
you have mentioned that Apple two datasets are taken from Twitter before and after quarterly earnings report. Could you please let us know what quarter is that? I mean is it after the 1, 2, 3 or fourth quarter the data was taken???
Longitude and Latitude is only available for those Twitter users who agree to share their location. Due to privacy reasons many people do not like to share their location and that's why majority of tweets do not have this info.
replyToSN - reply to Screenname
replyToSID - reply to sender ID
apple2.csv has data for 2nd quarter of 2017.
hi, your video is good and very useful for me. can you please provide how to get file from twitter and iam new to work on R software. if you don't mind i need some basic videos step by step process from getting data and doing wordcloud and sentiment analysis on R. i am waiting for your reply
for example i need a data from twitter big data in agriculture. like that i want to get data sheet from twitter and run the word cloud and sentiment analysis on R. can you suggest me
You can try these playlists:
ua-cam.com/play/PL34t5iLfZddt0tt5GdDy3ny6X5RQvwrp6.html
ua-cam.com/play/PL34t5iLfZddtfgOcE6aKCEXWtCkolpgjV.html
what do i do if i want to save the score in that csv file? or replace the reviews with the score in the file? Please Help.
Let's say your twitter data is in apple. Let's say you have all sentiment scores in SCORES. Then you can combine them using cbind(apple, SCORES). It will combine the columns.
Dr. Bharatendra Rai will try this. Thank you so much
welcome!
Thank you sir for simple tutorial on sentiment analysis.it is really helpful for me. sir kindly share the link from where i can download this apple.csv file to continue my work in R I need your help sir
A link should be available in the description area below this video.
@@bkrai oh i did not see this description thank you for your reply
Mr.Bharat, when i want now to pull new data about apple from Twitter , R returns the tweets dated 2018. My question is: how can i pull tweets ,for example, about the second quarter 2016? Is there any way to specify an exact date range to pull tweets? Regards.
Twitter has some restrictions about how much and how often you can pull data. It only allows you to go back few weeks from current date.
Hi Sir in TermdocumentMatrix ---Cleanset is not coming ,do we need to install any separate package for it?
Make sure in TermdocumentMatrix, 'D' is uppercase like 'TermDocumentMatrix.
@@bkrai done sir
Thank you very much ... sir we are facing many issues in openNLP package ... request you to kindly help us in getting some insight on the same also ..
I've not used openNLP.
Can I know the issues you are facing? Thanks in advance..
Hi! I have a question
While trying to plot the wordcloud I get this message:
hertha could not be fit on page. It will not be plotted.
6: In wordcloud(words = names(w), freq = w, max.words = 100, min.freq = 5, :
Any way I can fix it?
You can control how big or small a word looks using scale function as shown in the video.
Thank you for this wonderful video. I am a beginner in R. How do I get more of your tutorial videos on R.
You can find useful links in the description area of this video:
ua-cam.com/video/SOcPYdO22xM/v-deo.html
Hello. Which sentiment analysis package do you use?
syuzhet
Sir, can you explain this sentiment analysis and decision tree model are same or not?
They are different. Here is the link to decision tree:
ua-cam.com/video/tU3Adlru1Ng/v-deo.html
Hello Sir, I have imported all the mentioned libraries, but when I run the command: get_nrc_sentiment, I am getting the error as:
Error: 'vec_as_subscript' is not an exported object from 'namespace:vctrs'
Run `rlang::last_error()` to see where the error occurred.
Can you please help
Check structure of your data and make sure it is in right format.
Hey, i super appreciate to your work it easy to understand, but i have questions is that code can be implemented on any language such as Bahasa Indonesia?
Thanks you, if you are available for reply
I'll look into it.
thank you very much for this helpful tutorial. But is it possible to display this plot on a shiny app as an image? Can I store this plot in a variable and display it on a shiny app.
It should work fine.
Thank you so much, Rai.
You are welcome!
Sir, unable to perform sentiment analysis due to unavailability of package syuzhet and lubridate.... others like ggplot,scales are there... R is showing error displaying there is no packages named syuzhet and lubridate... what to do Sir.. plz help..
You need to install those packages first.
Sir, may i know how did you get "apple2.csv" ?
i.e how did you extract data (apple2.csv) after earnings ?
Here is the link to get tweets in csv file: ua-cam.com/video/QETCjkQ3CBw/v-deo.html
Sir, can u plz tell me why "utf-8-mac" was used in the beginning of the program.
If you are using a Mac computer, you can use it for the correct format needed.
@@bkrai Thank You Sir. Also is there any command which has to be used for format conversion in Windows?
Can you tell me how can I replace all special letters Or remove all special letters?
Could you please show us how to generate word cloud positive, word cloud negative separately
Thanks, I've added it to my list.
Sir, do we need to start with downloading packages? Some websites start with downloading or packages like sentimentR and others.
Yes you should install packages that are needed. And then run the library line.
@@bkrai thank you sir.
sir i am having problem in sentiment analysis! when i try to run the statement get_nrc_sentiment(tweets) it is showing error in .dataframe and error states undefined colums selected. and when i try to run head (s) it shows object not found. please let me know asap. thanks
What if there is an interesting word in the WordCloud. Is it possible to find from which tweet it came from? to localize it basically,
Such a word is likely to be from several tweets. You can know which tweets it came from using the Term Document Matrix.
Sir while trying this example my TermDocumentMatrix is not working...system gets hanged when the function is called
It may happen if data size is to big to be handled by your computer. Try reducing data size. Or you can try google colab:
ua-cam.com/video/XVfn6IpoUPU/v-deo.html
Hi! Thanks a lot for your video! I have a question. How do I remove stopwords for German? Is it the same line of code with putting german instead of english?
Thanks
This video is very helpful and could explain z test on r
I've used z-test in this:
ua-cam.com/video/oxRy2DMrOF4/v-deo.html
I am getting the below waring messages, how can I ignore this
Warning message:
In tm_map.SimpleCorpus(corpus, tolower) : transformation drops documents
You can check the matrix and see if you are really losing anything.
Thanks for your knowledge Share. Your explanation helps me a lot to achieve my goal. However, when I ran the scripts
corpus
Check if you ran library(tm) line or not.
Sir, i ran Library (tm) also on window but getting Error in iconv(apple$text, to = "utf-win") :
unsupported conversion from '' to 'utf-win' in codepage 1252. pl help me .
even corpus function is also not working
utf8text