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Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
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STOCK: 01/02/2017 LAST_PRICE: 0.0062835801737152 PX_VOLUME: 10.369000000000002 VOLATILITY_10D: 9.245 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters
|
Predicted 1_DAY_RETURN: 0.0035900351057349
Predicted 2_DAY_RETURN: 0.009425370260573
Predicted 7_DAY_RETURN: 693341.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @BambooParadise: 10x14 FRUIT Pear Plum Grapes Stained Art Glass Suncatcher #SilverCreek https://t.co/1vcQOKVc0k via @eBay" STOCK: nan DATE: nan
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
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Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
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STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
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The stock shows a neutral return trend over the specified periods.
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Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
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Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
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Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
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TWEET: "eBay" STOCK: 01/02/2017 DATE: 32.18
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @eBay.
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Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: 01/02/2017 1_DAY_RETURN: -0.000310752019888 2_DAY_RETURN: 0.0102548166563082 3_DAY_RETURN: -0.0605966438781851 7_DAY_RETURN: 9700776.0
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The stock shows a consistent positive return trend over the specified periods.
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Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: -0.0108763206960845 PX_VOLUME: 33.037 VOLATILITY_10D: 22.838 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay
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Predicted 1_DAY_RETURN: -0.000310752019888
Predicted 2_DAY_RETURN: 0.0102548166563082
Predicted 7_DAY_RETURN: 9700776.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
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TWEET: "#Collectible Leonardo DiCaprio 1999 Wall #Calendar Photos by Greg Gorman. https://t.co/stUGeCWDoa via @eBay #LeoDiCaprio #GregGorman" STOCK: nan DATE: nan
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
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Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
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STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
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The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
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Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "eBay" STOCK: 01/02/2017 DATE: 32.18
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @eBay.
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Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: 01/02/2017 1_DAY_RETURN: -0.000310752019888 2_DAY_RETURN: 0.0102548166563082 3_DAY_RETURN: -0.0605966438781851 7_DAY_RETURN: 9700776.0
|
The stock shows a consistent positive return trend over the specified periods.
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Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: -0.0108763206960845 PX_VOLUME: 33.037 VOLATILITY_10D: 22.838 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay
|
Predicted 1_DAY_RETURN: -0.000310752019888
Predicted 2_DAY_RETURN: 0.0102548166563082
Predicted 7_DAY_RETURN: 9700776.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @trvo512: are you fucking kidding me? @McDonalds https://t.co/YgNCoLqJhr" STOCK: nan DATE: nan
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
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STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
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The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
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Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "McDonald's" STOCK: 01/02/2017 DATE: 122.42
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -0.6 and the TextBlob polarity score is @McDonalds.
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Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
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STOCK: 01/02/2017 1_DAY_RETURN: 0.004901159941186 2_DAY_RETURN: 0.0035941839568697 3_DAY_RETURN: -0.0051462179382453 7_DAY_RETURN: 3233576.0
|
The stock shows a consistent positive return trend over the specified periods.
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Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: 0.0012252899852964 PX_VOLUME: 7.607 VOLATILITY_10D: 9.573 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.6 TEXTBLOB_POLARITY: @McDonalds
|
Predicted 1_DAY_RETURN: 0.004901159941186
Predicted 2_DAY_RETURN: 0.0035941839568697
Predicted 7_DAY_RETURN: 3233576.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @loadsofvans: Retweet this post & follow @loadsofvans for a chance to win a £100 @amazon voucher #win #giveaway #competition… " STOCK: nan DATE: nan
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
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STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
|
The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
|
Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "Amazon" STOCK: 01/02/2017 DATE: 832.35
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.8 and the TextBlob polarity score is @amazon.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: 01/02/2017 1_DAY_RETURN: -0.0023667928155223 2_DAY_RETURN: 0.0041088484411605 3_DAY_RETURN: 0.0050099116958009 7_DAY_RETURN: 3850181.0
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: -0.0106565747582146 PX_VOLUME: 14.201 VOLATILITY_10D: 16.989 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.8 TEXTBLOB_POLARITY: @amazon
|
Predicted 1_DAY_RETURN: -0.0023667928155223
Predicted 2_DAY_RETURN: 0.0041088484411605
Predicted 7_DAY_RETURN: 3850181.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @JReyno99: Hi @Google, just thought I'd let you know that you're clearly fucking wrong. #BWFC https://t.co/9zmeW8ecM1
" STOCK: Google DATE: 01/02/2017
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is -0.5.
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Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: Google 1_DAY_RETURN: 0.0060718316078701 2_DAY_RETURN: 0.0105367744467887 3_DAY_RETURN: 0.0365413865855453 7_DAY_RETURN: 0.0530027967224376
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: Google LAST_PRICE: 815.24 PX_VOLUME: 2251047.0 VOLATILITY_10D: 21.579 VOLATILITY_30D: 15.049 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: -0.5
|
Predicted 1_DAY_RETURN: 0.0060718316078701
Predicted 2_DAY_RETURN: 0.0105367744467887
Predicted 7_DAY_RETURN: 0.0530027967224376
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "Check out Banana Republic Black Pleated Faux Leather Cropped Ankle Pants Sz 8 #BananaRepublic https://t.co/waWURhqtM8 via @eBay" STOCK: nan DATE: nan
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
|
The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
|
Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "eBay" STOCK: 01/02/2017 DATE: 32.18
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -0.16666666666666666 and the TextBlob polarity score is @eBay.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: 01/02/2017 1_DAY_RETURN: -0.000310752019888 2_DAY_RETURN: 0.0102548166563082 3_DAY_RETURN: -0.0605966438781851 7_DAY_RETURN: 9700776.0
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: -0.0108763206960845 PX_VOLUME: 33.037 VOLATILITY_10D: 22.838 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.16666666666666666 TEXTBLOB_POLARITY: @eBay
|
Predicted 1_DAY_RETURN: -0.000310752019888
Predicted 2_DAY_RETURN: 0.0102548166563082
Predicted 7_DAY_RETURN: 9700776.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @trvo512: are you fucking kidding me? @McDonalds https://t.co/YgNCoLqJhr" STOCK: nan DATE: nan
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
|
The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
|
Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "McDonald's" STOCK: 01/02/2017 DATE: 122.42
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -0.6 and the TextBlob polarity score is @McDonalds.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: 01/02/2017 1_DAY_RETURN: 0.004901159941186 2_DAY_RETURN: 0.0035941839568697 3_DAY_RETURN: -0.0051462179382453 7_DAY_RETURN: 3233576.0
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: 0.0012252899852964 PX_VOLUME: 7.607 VOLATILITY_10D: 9.573 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.6 TEXTBLOB_POLARITY: @McDonalds
|
Predicted 1_DAY_RETURN: 0.004901159941186
Predicted 2_DAY_RETURN: 0.0035941839568697
Predicted 7_DAY_RETURN: 3233576.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "@2ndamendment19 @shaunz4 @trump_dopey @protesthate @KeyMrB @AmyMek @Starbucks I'm done, go troll someone else or talk among yourselves.
" STOCK: Starbucks DATE: 01/02/2017
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: Starbucks 1_DAY_RETURN: 0.0244897959183673 2_DAY_RETURN: 0.0371057513914656 3_DAY_RETURN: 0.0411873840445268 7_DAY_RETURN: 0.0890538033395177
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: Starbucks LAST_PRICE: 53.9 PX_VOLUME: 18796871.0 VOLATILITY_10D: 25.781 VOLATILITY_30D: 18.576 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
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Predicted 1_DAY_RETURN: 0.0244897959183673
Predicted 2_DAY_RETURN: 0.0371057513914656
Predicted 7_DAY_RETURN: 0.0890538033395177
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Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "@WellsFargo
45 minutes on hold and then told unfortunately there is no one to take your call good bye. #NoCustomerService
" STOCK: Wells Fargo DATE: 01/02/2017
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.09999999999999998.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: Wells Fargo 1_DAY_RETURN: 0.0075120729744232 2_DAY_RETURN: 0.0030406009658379 3_DAY_RETURN: 0.0121624038633519 7_DAY_RETURN: 0.012698980504382
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: Wells Fargo LAST_PRICE: 55.91 PX_VOLUME: 21157698.0 VOLATILITY_10D: 24.594 VOLATILITY_30D: 20.199 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.09999999999999998
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Predicted 1_DAY_RETURN: 0.0075120729744232
Predicted 2_DAY_RETURN: 0.0030406009658379
Predicted 7_DAY_RETURN: 0.012698980504382
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Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @RisingSilent: So @Starbucks just to be clear, you'll only be hiring the friendly Muslims like the one on the left, correct?…
" STOCK: Starbucks DATE: 01/02/2017
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.11875.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: Starbucks 1_DAY_RETURN: 0.0244897959183673 2_DAY_RETURN: 0.0371057513914656 3_DAY_RETURN: 0.0411873840445268 7_DAY_RETURN: 0.0890538033395177
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: Starbucks LAST_PRICE: 53.9 PX_VOLUME: 18796871.0 VOLATILITY_10D: 25.781 VOLATILITY_30D: 18.576 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.11875
|
Predicted 1_DAY_RETURN: 0.0244897959183673
Predicted 2_DAY_RETURN: 0.0371057513914656
Predicted 7_DAY_RETURN: 0.0890538033395177
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "Check out Kimono: Japanese Style Designs--Flowers, Animals, Nature (Designer's Notebook, 2 https://t.co/hH0hVEoZqe via @eBay
" STOCK: eBay DATE: 01/02/2017
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: eBay 1_DAY_RETURN: -0.0108763206960845 2_DAY_RETURN: -0.000310752019888 3_DAY_RETURN: 0.0102548166563082 7_DAY_RETURN: -0.0605966438781851
|
The stock shows a consistent negative return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: eBay LAST_PRICE: 32.18 PX_VOLUME: 9700776.0 VOLATILITY_10D: 33.037 VOLATILITY_30D: 22.838 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
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Predicted 1_DAY_RETURN: -0.0108763206960845
Predicted 2_DAY_RETURN: -0.000310752019888
Predicted 7_DAY_RETURN: -0.0605966438781851
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "@markb44333 @Sheasy64 @mattdpearce @Reuters WHITE NATIONALISM WAS GOOD WHILE IT LASTED FOR THIS FIRST WEEK - DOWN, DOWN, DOWN...
" STOCK: Reuters DATE: 01/02/2017
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Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.08055555555555555.
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Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: Reuters 1_DAY_RETURN: 0.0062835801737152 2_DAY_RETURN: 0.0035900351057349 3_DAY_RETURN: 0.009425370260573 7_DAY_RETURN: 0.0177280904965943
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
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STOCK: Reuters LAST_PRICE: 49.0803 PX_VOLUME: 693341.0 VOLATILITY_10D: 10.369000000000002 VOLATILITY_30D: 9.245 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.08055555555555555
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Predicted 1_DAY_RETURN: 0.0062835801737152
Predicted 2_DAY_RETURN: 0.0035900351057349
Predicted 7_DAY_RETURN: 0.0177280904965943
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @pepsi: We’ve got @LadyGaga’s #PepsiHalftime show under the 🔬 and it’s looking 🔥🔥🔥. Check out this #BehindTheScenes 📹 👆of h… " STOCK: nan DATE: nan
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
|
The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
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Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "Pepsi" STOCK: 01/02/2017 DATE: 103.01
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @pepsi.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: 01/02/2017 1_DAY_RETURN: 0.0066013008445781 2_DAY_RETURN: 0.0045626638190466 3_DAY_RETURN: 0.015532472575478 7_DAY_RETURN: 3515578.0
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: 0.0074750024269488 PX_VOLUME: 9.724 VOLATILITY_10D: 8.722000000000001 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @pepsi
|
Predicted 1_DAY_RETURN: 0.0066013008445781
Predicted 2_DAY_RETURN: 0.0045626638190466
Predicted 7_DAY_RETURN: 3515578.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "@FoxNews @Starbucks @FoxNewsInsider PS: don't forget to fix the report about the mosque: White. Nationalist. Terrorist." STOCK: nan DATE: nan
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
|
The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
|
Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "Starbucks" STOCK: 01/02/2017 DATE: 53.9
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Starbucks.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: 01/02/2017 1_DAY_RETURN: 0.0371057513914656 2_DAY_RETURN: 0.0411873840445268 3_DAY_RETURN: 0.0890538033395177 7_DAY_RETURN: 18796871.0
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: 0.0244897959183673 PX_VOLUME: 25.781 VOLATILITY_10D: 18.576 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks
|
Predicted 1_DAY_RETURN: 0.0371057513914656
Predicted 2_DAY_RETURN: 0.0411873840445268
Predicted 7_DAY_RETURN: 18796871.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "Check out LIZ CLAIBORNE LIZWEAR JEANS SHIRT RED Stripe, XL Women's, Sleeveless 90's Style #Casual https://t.co/dQBy2pxyv6 via @eBay
" STOCK: eBay DATE: 01/02/2017
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -1 and the TextBlob polarity score is 0.0.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: eBay 1_DAY_RETURN: -0.0108763206960845 2_DAY_RETURN: -0.000310752019888 3_DAY_RETURN: 0.0102548166563082 7_DAY_RETURN: -0.0605966438781851
|
The stock shows a consistent negative return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: eBay LAST_PRICE: 32.18 PX_VOLUME: 9700776.0 VOLATILITY_10D: 33.037 VOLATILITY_30D: 22.838 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
|
Predicted 1_DAY_RETURN: -0.0108763206960845
Predicted 2_DAY_RETURN: -0.000310752019888
Predicted 7_DAY_RETURN: -0.0605966438781851
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @CieloChulacielo: @netflix #BATB This show lends itself to so many story possibilities, that are still left to be told…
" STOCK: Netflix DATE: 01/02/2017
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.25.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: Netflix 1_DAY_RETURN: -0.0004972297201306 2_DAY_RETURN: 0.0031254439551072 3_DAY_RETURN: 0.0118624804659751 7_DAY_RETURN: -0.0089501349623525
|
The stock shows a consistent negative return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: Netflix LAST_PRICE: 140.78 PX_VOLUME: 6033422.0 VOLATILITY_10D: 19.491 VOLATILITY_30D: 24.09800000000001 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.25
|
Predicted 1_DAY_RETURN: -0.0004972297201306
Predicted 2_DAY_RETURN: 0.0031254439551072
Predicted 7_DAY_RETURN: -0.0089501349623525
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @Drops: yo fuck you @McDonalds https://t.co/NEUCDMBGMe" STOCK: nan DATE: nan
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
|
The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
|
Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "McDonald's" STOCK: 01/02/2017 DATE: 122.42
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -0.4 and the TextBlob polarity score is @McDonalds.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: 01/02/2017 1_DAY_RETURN: 0.004901159941186 2_DAY_RETURN: 0.0035941839568697 3_DAY_RETURN: -0.0051462179382453 7_DAY_RETURN: 3233576.0
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: 0.0012252899852964 PX_VOLUME: 7.607 VOLATILITY_10D: 9.573 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.4 TEXTBLOB_POLARITY: @McDonalds
|
Predicted 1_DAY_RETURN: 0.004901159941186
Predicted 2_DAY_RETURN: 0.0035941839568697
Predicted 7_DAY_RETURN: 3233576.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @Reuters: EU chair labels Trump a 'threat' as Europeans debate U.S. ties https://t.co/pA5fO15epw https://t.co/FMeV4Oyh8t" STOCK: nan DATE: nan
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
|
The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
|
Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "Reuters" STOCK: 01/02/2017 DATE: 49.0803
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Reuters.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: 01/02/2017 1_DAY_RETURN: 0.0035900351057349 2_DAY_RETURN: 0.009425370260573 3_DAY_RETURN: 0.0177280904965943 7_DAY_RETURN: 693341.0
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: 0.0062835801737152 PX_VOLUME: 10.369000000000002 VOLATILITY_10D: 9.245 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters
|
Predicted 1_DAY_RETURN: 0.0035900351057349
Predicted 2_DAY_RETURN: 0.009425370260573
Predicted 7_DAY_RETURN: 693341.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @nikitakhara: Thank you, @Starbucks CEO for committing to hire 10,000 refugees.
To all those tweeting #boycottstarbucks, thanks for the…
" STOCK: Starbucks DATE: 01/02/2017
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.2.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: Starbucks 1_DAY_RETURN: 0.0244897959183673 2_DAY_RETURN: 0.0371057513914656 3_DAY_RETURN: 0.0411873840445268 7_DAY_RETURN: 0.0890538033395177
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: Starbucks LAST_PRICE: 53.9 PX_VOLUME: 18796871.0 VOLATILITY_10D: 25.781 VOLATILITY_30D: 18.576 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.2
|
Predicted 1_DAY_RETURN: 0.0244897959183673
Predicted 2_DAY_RETURN: 0.0371057513914656
Predicted 7_DAY_RETURN: 0.0890538033395177
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @Reuters: Challenges to Trump's immigration orders spread to more U.S. states https://t.co/SuOdXe1cr7 https://t.co/YZte1JNu1G" STOCK: nan DATE: nan
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
|
The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
|
Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "Reuters" STOCK: 01/02/2017 DATE: 49.0803
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.5 and the TextBlob polarity score is @Reuters.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: 01/02/2017 1_DAY_RETURN: 0.0035900351057349 2_DAY_RETURN: 0.009425370260573 3_DAY_RETURN: 0.0177280904965943 7_DAY_RETURN: 693341.0
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: 01/02/2017 LAST_PRICE: 0.0062835801737152 PX_VOLUME: 10.369000000000002 VOLATILITY_10D: 9.245 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.5 TEXTBLOB_POLARITY: @Reuters
|
Predicted 1_DAY_RETURN: 0.0035900351057349
Predicted 2_DAY_RETURN: 0.009425370260573
Predicted 7_DAY_RETURN: 693341.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "I think @Starbucks should create a new drink, the #TrumpWhoopachino. Two sizes, Bigly and Yuge. All profits donated to the @ACLU.
" STOCK: Starbucks DATE: 01/02/2017
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.13636363636363635.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: Starbucks 1_DAY_RETURN: 0.0244897959183673 2_DAY_RETURN: 0.0371057513914656 3_DAY_RETURN: 0.0411873840445268 7_DAY_RETURN: 0.0890538033395177
|
The stock shows a consistent positive return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: Starbucks LAST_PRICE: 53.9 PX_VOLUME: 18796871.0 VOLATILITY_10D: 25.781 VOLATILITY_30D: 18.576 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.13636363636363635
|
Predicted 1_DAY_RETURN: 0.0244897959183673
Predicted 2_DAY_RETURN: 0.0371057513914656
Predicted 7_DAY_RETURN: 0.0890538033395177
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "@MarketWatch BULL SHIT @peterthiel @facebook @Uber @TeslaMotors @Apple" STOCK: nan DATE: nan
|
Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan
|
The stock shows a neutral return trend over the specified periods.
|
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
|
STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan
|
Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan
|
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