File processing
Input format: Input files must be in .txt FORMAT with UTF-8 ENCODING and contain PORTUGUESE TEXT. Input files and folders can also be compressed to the .zip format.
Privacy: The input file you upload and the respective output files will be automatically deleted from our computer after being processed and the result downloaded by you. No copies of your files will be retained after your use of this service.
Email address validation
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The size of your input file is large and its processing may take some time.
To receive by email an URL from which to download your processed file, please copy the code displayed below into the field "Subject:" of an email message (with the message body empty) and send it to request@portulanclarin.net
To proceed, please send an email to request@portulanclarin.net with the following code in the "Subject" field:
To: | request@portulanclarin.net |
|
Subject: |
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Privacy: After we reply to you with the URL for download, your email address is automatically deleted from our records.
Instructions to use this web service
The web service for this application is available at https://portulanclarin.net/workbench/uevora-sentiment-analysis/api/.
Below you find an example of how to use this web service with Python 3.
This example resorts to the requests package. To install this package, run this command in the command line:
pip3 install requests
.
To use this web service, you need an access key you can obtain by clicking in the button below. A key is valid for 31 days. It allows to submit a total of 1 billion characters by means of requests with no more 4000 characters each. It allows to enter 100,000 requests, at a rate of no more than 200 requests per hour.
For other usage regimes, you should contact the helpdesk.
The input data and the respective output will be automatically deleted from our computer after being processed. No copies will be retained after your use of this service.
import json
import requests # to install this library, enter in your command line:
# pip3 install requests
# This is a simple example to illustrate how you can use the VISTA@UE-SA web service
# Requires: key is a string with your access key
# Requires: text is a string, UTF-8, with a maximum 4000 characters, Portuguese text, with
# the input to be processed
# Requires: format is a string, indicating the output format, which can be either
# 'column' or 'JSON'
# Ensures: output according to specification in
# https://portulanclarin.net/workbench/uevora-sentiment-analysis/
# Ensures: dict with number of requests and characters input so far with the access key, and
# its date of expiry
key = 'access_key_goes_here' # before you run this example, replace access_key_goes_here by
# your access key
# this string can be replaced by your input
text = '''Um livro maravilhoso que toda a gente, que gosta de um bom mistério, deve ler.
Achei o restaurante ruidoso e o serviço era lento.
A sobremesa de mousse de chocolate era muito saborosa.
O filme era longo e aborrecido.
'''
# To read input text from a file, uncomment this block
#inputFile = open("myInputFileName", "r", encoding="utf-8") # replace myInputFileName by
# the name of your file
#text = inputFile.read()
#inputFile.close()
format = 'column' # other possible value is 'JSON'
# Processing:
url = "https://portulanclarin.net/workbench/uevora-sentiment-analysis/api/"
request_data = {
'method': 'analyse',
'jsonrpc': '2.0',
'id': 0,
'params': {
'text': text,
'format': format,
'key': key,
},
}
request = requests.post(url, json=request_data)
response_data = request.json()
if "error" in response_data:
print("Error:", response_data["error"])
else:
print("Result:")
print(response_data["result"])
# To write output in a file, uncomment this block
#outputFile = open("myOutputFileName","w", encoding="utf-8") # replace myOutputFileName by
# the name of your file
#output = response_data["result"]
#outputFile.write(output)
#outputFile.close()
# Getting acess key status:
request_data = {
'method': 'key_status',
'jsonrpc': '2.0',
'id': 0,
'params': {
'key': key,
},
}
request = requests.post(url, json=request_data)
response_data = request.json()
if "error" in response_data:
print("Error:", response_data["error"])
else:
print("Key status:")
print(json.dumps(response_data["result"], indent=4))
Access key for the web service
This is your access key for this web service.
The following access key for this web service is already associated with .
This key is valid until and can be used to process requests or characters.
An email message has been sent into your address with the information above.
Email address validation
Loading...
To receive by email your access key for this webservice, please copy the code displayed below into the field "Subject" of an email message (with the message body empty) and send it to request@portulanclarin.net
To proceed, please send an email to request@portulanclarin.net with the following code in the "Subject" field:
To: | request@portulanclarin.net |
|
Subject: |
|
The communication with the server cannot be established. Please try again later.
We are sorry but an unexpected error has occurred. Please try again later.
The code has expired. Please click the button below to get a new code.
For enhanced security, a new code has to be validated. Please click the button below to get a new code.
Privacy: When your access key expires, your email address is automatically deleted from our records.
VISTA@UE-SA's documentation
Functionality
VISTA@UE-SA is a freely available on-line service for the sentiment analysis of short sentences (tweets) in Portuguese. This service was developed and is maintained at the University of Evora by the VISTA - Video, Image, Speech, and Text Analysis Group of the Department of Informatics.
The VISTA@UE-SA is based on a machine learning methodology and it used a collection of previously classified tweets as a training set.
Authorship
VISTA@UE-SA was developed by Paulo Quaresma at the VISTA@UE research group.
License
To use VISTA@UE-SA you must accept the terms of this license.
Release
Presently VISTA@UE-SA cannot be downloaded.
Reference
The VISTA@UE-SA description and evaluation is not yet published.
However, some of the datasets used to learn the classifier model were published or are available online:
1. A dataset created in 2017 by Henrico Brum, MSc student at University of Sao Paulo - ICMC. Further description of the method is available in the paper "Building a Sentiment Corpus of Tweets in Brazilian Portuguese" (BRUM, H. B. and NUNES, M. G. V., 2018) presented at the 20th Language Resources and Evaluation Conference in Miyazaki, Japan on 2018.
2. A dataset created by Rodrigo Santana, MSc student in Computer Science.
Contact us
Contact us using the following email address: pq@uevora.pt
License
No fee, attribution, all rights reserved, no redistribution, non commercial, no warranty, no liability, no endorsement, temporary, non exclusive, share alike.
The complete text of this license is here.