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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
|
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.
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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 -0.4 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.
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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 @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.
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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: "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: "VR Mask Virtual Reality Viewer - 3D Five Below Merchandising https://t.co/YlnOzd4fzP via @amazon" 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.
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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.
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TWEET: "Amazon" STOCK: 01/02/2017 DATE: 832.35
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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 @amazon.
|
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: -0.0023667928155223 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: 0.0 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 @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: "RT @StuFowle: Hey, everybody watch the @CBS Super Bowl special on right now to see this year's new @Buick ad for the first time
" STOCK: CBS 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 0.2725108225108225.
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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: CBS 1_DAY_RETURN: -0.0017027863777089 2_DAY_RETURN: -0.0030959752321979 3_DAY_RETURN: 0.0021671826625387 7_DAY_RETURN: -0.024767801857585
|
The stock shows a consistent negative 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: CBS LAST_PRICE: 64.6 PX_VOLUME: 2123243.0 VOLATILITY_10D: 13.477 VOLATILITY_30D: 16.281 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.2725108225108225
|
Predicted 1_DAY_RETURN: -0.0017027863777089
Predicted 2_DAY_RETURN: -0.0030959752321979
Predicted 7_DAY_RETURN: -0.024767801857585
|
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: "RT @Reuters: Warren Buffett: I bought $12 billion of stock after Trump won https://t.co/pJeydK14Sh https://t.co/AAoFa4bbZh" 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 @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: "@georganneb @Starbucks they have already lost me and my daily meeting." 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: "No more @facebook ... deleted and everything. Very liberating follow me on Twitter @Brucesmitty79" 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.
|
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: "Facebook" STOCK: 01/02/2017 DATE: 133.23
|
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 -0.25 and the TextBlob polarity score is @facebook.
|
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: -0.016888088268408 2_DAY_RETURN: -0.0078811078585902 3_DAY_RETURN: -0.0131351797643173 7_DAY_RETURN: 50139775.0
|
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: -0.0218419274938076 PX_VOLUME: 18.12 VOLATILITY_10D: 16.992 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.25 TEXTBLOB_POLARITY: @facebook
|
Predicted 1_DAY_RETURN: -0.016888088268408
Predicted 2_DAY_RETURN: -0.0078811078585902
Predicted 7_DAY_RETURN: 50139775.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "@Reuters the picture is too small to see on an iPhone
republicans are stupid as this statistics shows
" STOCK: Reuters 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 -0.5249999999999999.
|
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.
|
STOCK: Reuters LAST_PRICE: 49.0803 PX_VOLUME: 693341.0 VOLATILITY_10D: 10.369000000000002 VOLATILITY_30D: 9.245 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: -0.5249999999999999
|
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 @Reuters: Warren Buffett: I bought $12 billion of stock after Trump won https://t.co/pJeydK14Sh https://t.co/AAoFa4bbZh" 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 @Reuters: Trump #SCOTUS nominee Gorsuch could influence the direction of the court for decades https://t.co/c7eY8DFFWw https://t.co/6FgM…" 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 @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: "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: "@toastyH1Z1 @Zurvanism @RedxBreIlaZ @McDonalds well it's tasty either way at least to me" 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 -0.3 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: -0.3 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 @BtuflyBoutique: Qsquared White Hi Gloss Ruffle Collection 10.5" Diameter Round Dinner Plate https://t.co/PmcT9flzXq @eBay https://t.co/…
" 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 -0.1.
|
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: -0.1
|
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 @neymarjr: Glad to see another champion on team @Gillette. Welcome, @xPekeLoL.
#PursuitofPrecision https://t.co/q4RdjwvJyN
" STOCK: Gillette 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.
|
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
|
STOCK: Gillette 1_DAY_RETURN: 0.0001778536620069 2_DAY_RETURN: 0.0018378211740713 3_DAY_RETURN: 0.0011382634368442 7_DAY_RETURN: 0.0012686894556493
|
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: Gillette LAST_PRICE: 4216.95 PX_VOLUME: 3863.0 VOLATILITY_10D: 3.391 VOLATILITY_30D: 4.525 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.5
|
Predicted 1_DAY_RETURN: 0.0001778536620069
Predicted 2_DAY_RETURN: 0.0018378211740713
Predicted 7_DAY_RETURN: 0.0012686894556493
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @Disney: Rediscover the timeless tale of #BeautyAndTheBeast March 17. Tickets are now available: https://t.co/S6wwuIfygP https://t.co/uY…" 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: "Disney" STOCK: 01/02/2017 DATE: 111.3
|
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 @Disney.
|
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: -0.0032345013477088 2_DAY_RETURN: -0.017969451931716 3_DAY_RETURN: -0.0292902066486971 7_DAY_RETURN: 10501334.0
|
The stock shows a consistent positive return trend over the specified periods.
|
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