6

Amazon has an API for this, and then there's always web-scraping.


5

Could you explain more about what you need the data for? I'm not aware of any pre-built data sets, but you could attempt to construct your own. You'll need to break the problem into two parts though. The easiest route to identifying the entities is the OpenCalais API, which despite its name is a closed-source service, but has generous usage limits. You can ...


5

The first source of raw interactions that fit your needs that comes to mind is Twitter. NCSU's Tweet Sentiment Visualization http://www.csc.ncsu.edu/faculty/healey/tweet_viz/tweet_app/ seems pretty good in that it allows you to enter keywords and get a graph of recent tweets graphed on axes (pleasant/unpleasant and active/inactive). It also has some pretty ...


5

We have several product reviews indexed at https://www.datafiniti.net. Here is a search for every product we have with reviews: link. Many reviews have text, title, date, rating, etc.


5

I found NRC Word-Emotion Association Lexicon has something that I was looking for. The NRC Emotion Lexicon is a list of English words and their associations with eight basic emotions (anger, fear, anticipation, trust, surprise, sadness, joy, and disgust) and two sentiments (negative and positive). The annotations were manually done by crowdsourcing.


4

467 million Twitter posts from 20 million users covering a 7 month period from June 1 2009 to December 31 2009. We estimate this is about 20-30% of all public tweets published on Twitter during the particular time frame. For each public tweet the following information is available: Author Time Content Please refer this link: https://snap.stanford.edu/data/...


4

Some nice data sets for practicing sentiment classification are: Sentiment 140 Tweets2011 Dataset by Sanders Another source This one on Github One from a Kaggle contest EMOTIONAL SENSOR DATA SET 1.0.8 These are some open datasets which contain emotions like happy, sad, etc: Affective Sciences (Data in .sav data files)


3

Reddit Comment Dataset Including Sentiment Data


3

Here is a dataset of Amazon product reviews - nearly 150 reviews spanning 8 years across various products http://jmcauley.ucsd.edu/data/amazon/


3

There are 3 things that are decreasing your search results count: The Twitter Search API only gives results about 1 week back. Only a fraction of tweets are geo-tagged. Search terms may be too specific. There isn't too much to do about 1 and 2, but for 3, I can recommend getting familiar with Advanced Search. You can construct a query with the website, ...


2

This would be a good data source and the researcher also done a work on it. refer it too. good luck


2

(Example) Spanish Language Corpora: ESCOW14 Project Gutenberg Any of the wiki projects starting with "es" - https://dumps.wikimedia.org/backup-index.html For example - https://dumps.wikimedia.org/eswiki/20150805/ http://www.corpusdelespanol.org/ Twitter API public stream with lang:es as stream filter - details Affective Word list for Spanish The Spanish ...


2

I have actually been working on something very similar; a search engine for restaurants in London. The search engine crawls popular social media platforms (TripAdvisor, Open Table etc.) on a daily basis and allows users to get an overall view for a given restaurant based on written comments from EVERY review. You can also search for a particular dish / ...


2

I would be tempted to use Google Finance or Yahoo Finance to get a list of stock symbols. i.e. VOD.L Then you could use the twitter API to extract search results for each one, again i.e. $VOD.L https://twitter.com/search?q=%24VOD.L There is a list of news APIs on Programmable Web that could perhaps be used to extract news items for each symbol: http://www....


2

As with many new areas of research, this doesn't seem to be a domain with much truly open data, but you may be able to contact academic researchers about using datasets they have compiled for their work. This W3C wiki page on sentiment analysis lists several such datasets. For example, the Center for the Study of Emotion and Attention at University of ...


2

Yes, please share this information with the world. Sentiment analysis is always desired, I see plenty of questions regarding sa, as well as seeking twitter datasets on here regularly. Don't worry about not wanting to build a site/maintain something/etc., sharing the data is entirely enough. As far as storage/sharing, you have a plethora of options, here's ...


1

In retail domain, you can find reviews of products from e-commerce sites. Sentiment analysis on the reviews of a product can be leveraged by the manufacturer for that product lifecycle management and/or in ideation of production of similar kind of a new product in the market.


1

Have a look at this http://xpresso.abzooba.com/XpressoOnWeb/ for aspect based sentimental analysis.


1

The best one I know is this: https://www.cs.cmu.edu/~./enron/ this is also available in MySQL format! https://www.cs.purdue.edu/homes/jpfeiff/enron.html It's the email corpus of Enron during the moments when it collapsed. The emails are clearly characterized by underlying feelings. This dataset is quite unique and heavily described in the podcast Linear ...


1

Why not you use Twitter Search API to search your particular type text, then do some text modification. Sorry, I am not expert, it is just an idea.


1

You can find Amazon reviews webdata 1995-2013 data on archive.org. This dataset consists of reviews from amazon. The data span a period of 18 years, including ~35 million reviews up to March 2013. Reviews include product and user information, ratings, and a plaintext review. Note: this dataset contains potential duplicates, due to products whose reviews ...


1

I found the MPQA Opinion corpus here: http://mpqa.cs.pitt.edu/ this is close to what I am looking for.


1

The FIRST corpus sounds like it might fit the bill. You might also look at the corpora used in similar research like Good News or Bad News? Let the Market Decide. A Google search along the lines of "sentiment analysis labeled news corpus" (without the quotes) might turn up some other relevant leads to follow. Putting a high quality corpus together is ...


1

I think the simplest answer would be to look at how articles are labelled by the news aggregators. If you go to http://newsnow.co.uk or https://news.google.com/ or http://www.moreover.com/ they aggregate news articles and then helpfully label them up to help you with sentiment.


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