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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: 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: "L'Oreal" STOCK: 31/01/2017 DATE: 181.1
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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 0.2 and the TextBlob polarity score is @Loreal.
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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: 31/01/2017 1_DAY_RETURN: 0.003865267807841 2_DAY_RETURN: 0.003865267807841 3_DAY_RETURN: 0.0117614577581446 7_DAY_RETURN: 89.0
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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.
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STOCK: 31/01/2017 LAST_PRICE: 0.003865267807841 PX_VOLUME: 11.972 VOLATILITY_10D: 20.54 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.2 TEXTBLOB_POLARITY: @Loreal
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Predicted 1_DAY_RETURN: 0.003865267807841
Predicted 2_DAY_RETURN: 0.003865267807841
Predicted 7_DAY_RETURN: 89.0
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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: "@peterwsinger @Ford after that unfortunate America First era passed all those years ago" 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.
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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: "Ford" STOCK: 31/01/2017 DATE: 12.36
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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 -0.125 and the TextBlob polarity score is @Ford.
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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: 31/01/2017 1_DAY_RETURN: 0.0105177993527508 2_DAY_RETURN: 0.0105177993527508 3_DAY_RETURN: 0.0202265372168284 7_DAY_RETURN: 46974479.0
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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.
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STOCK: 31/01/2017 LAST_PRICE: 0.0008090614886731 PX_VOLUME: 26.321 VOLATILITY_10D: 27.647 VOLATILITY_30D: 1.0 LSTM_POLARITY: -0.125 TEXTBLOB_POLARITY: @Ford
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Predicted 1_DAY_RETURN: 0.0105177993527508
Predicted 2_DAY_RETURN: 0.0105177993527508
Predicted 7_DAY_RETURN: 46974479.0
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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: "@cyberdayze
CyberDayze Page Publishing, Inc. https://t.co/82BibjdHLX via @amazon
" STOCK: Amazon DATE: 31/01/2017
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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.
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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: Amazon 1_DAY_RETURN: 0.0083790741730217 2_DAY_RETURN: 0.0149244668965851 3_DAY_RETURN: 0.0149244668965851 7_DAY_RETURN: -0.0012629329188322
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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.
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STOCK: Amazon LAST_PRICE: 823.48 PX_VOLUME: 3137196.0 VOLATILITY_10D: 13.447 VOLATILITY_30D: 16.992 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0
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Predicted 1_DAY_RETURN: 0.0083790741730217
Predicted 2_DAY_RETURN: 0.0149244668965851
Predicted 7_DAY_RETURN: -0.0012629329188322
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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: "Check out Earrings black glass pearl center with frosted glass crystal dangle chain style https://t.co/Xhtr87NqMH 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.
|
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.
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TWEET: "eBay" STOCK: 31/01/2017 DATE: 31.83
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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 -0.13333333333333333 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.
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STOCK: 31/01/2017 1_DAY_RETURN: 0.021363493559535 2_DAY_RETURN: 0.021363493559535 3_DAY_RETURN: -0.0578071002199183 7_DAY_RETURN: 9469076.0
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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.
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STOCK: 31/01/2017 LAST_PRICE: 0.0106817467797676 PX_VOLUME: 33.029 VOLATILITY_10D: 22.932 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.13333333333333333 TEXTBLOB_POLARITY: @eBay
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Predicted 1_DAY_RETURN: 0.021363493559535
Predicted 2_DAY_RETURN: 0.021363493559535
Predicted 7_DAY_RETURN: 9469076.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @Starbucks: @ScottBaio Thanks for your question! We’re proud to invest in and support minority communities like Ferguson, MO. https://t.…
" STOCK: Starbucks DATE: 31/01/2017
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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 0.25.
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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: Starbucks 1_DAY_RETURN: 0.0123143788482433 2_DAY_RETURN: 0.0162984425932632 3_DAY_RETURN: 0.0162984425932632 7_DAY_RETURN: 0.0583122057225642
|
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: 55.22 PX_VOLUME: 14307985.0 VOLATILITY_10D: 23.916 VOLATILITY_30D: 17.298 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.25
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Predicted 1_DAY_RETURN: 0.0123143788482433
Predicted 2_DAY_RETURN: 0.0162984425932632
Predicted 7_DAY_RETURN: 0.0583122057225642
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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 @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.
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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 -0.6 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.
|
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
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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: "Former @blackrock VP joins global #investment firm, https://t.co/eJkeZNWVYI https://t.co/3QkoxeJW0A
" STOCK: BlackRock 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 -0.06666666666666668.
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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: BlackRock 1_DAY_RETURN: 0.002627345844504 2_DAY_RETURN: 0.0058445040214477 3_DAY_RETURN: 0.0055227882037533 7_DAY_RETURN: 0.0410991957104557
|
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: BlackRock LAST_PRICE: 373.0 PX_VOLUME: 619442.0 VOLATILITY_10D: 20.305 VOLATILITY_30D: 17.352 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: -0.06666666666666668
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Predicted 1_DAY_RETURN: 0.002627345844504
Predicted 2_DAY_RETURN: 0.0058445040214477
Predicted 7_DAY_RETURN: 0.0410991957104557
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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: "@Google what would it take to get a website removed permanently from Google search thay steals & sells others content without permission?" 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
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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: "Google" STOCK: 01/02/2017 DATE: 815.24
|
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 @Google.
|
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: 0.0105367744467887 2_DAY_RETURN: 0.0365413865855453 3_DAY_RETURN: 0.0530027967224376 7_DAY_RETURN: 2251047.0
|
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: 0.0060718316078701 PX_VOLUME: 21.579 VOLATILITY_10D: 15.049 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Google
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Predicted 1_DAY_RETURN: 0.0105367744467887
Predicted 2_DAY_RETURN: 0.0365413865855453
Predicted 7_DAY_RETURN: 2251047.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "I talked betting with Siri. Gives spreads but no totals, including #SuperBowl. No pos on legalizing either. @Apple https://t.co/8xNonDb42z
" STOCK: Apple 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: Apple 1_DAY_RETURN: -0.0574757281553398 2_DAY_RETURN: -0.0553009708737864 3_DAY_RETURN: -0.0528155339805825 7_DAY_RETURN: -0.0533592233009709
|
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: Apple LAST_PRICE: 128.75 PX_VOLUME: 111985040.0 VOLATILITY_10D: 32.204 VOLATILITY_30D: 19.196 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
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Predicted 1_DAY_RETURN: -0.0574757281553398
Predicted 2_DAY_RETURN: -0.0553009708737864
Predicted 7_DAY_RETURN: -0.0533592233009709
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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 @fubaglady: SMOKING GUN: @Google Is Suppressing Center-Right News Sites https://t.co/fk0WOAXAsA Subversives." 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
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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: "Google" STOCK: 01/02/2017 DATE: 815.24
|
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 @Google.
|
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: 0.0105367744467887 2_DAY_RETURN: 0.0365413865855453 3_DAY_RETURN: 0.0530027967224376 7_DAY_RETURN: 2251047.0
|
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: 0.0060718316078701 PX_VOLUME: 21.579 VOLATILITY_10D: 15.049 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Google
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Predicted 1_DAY_RETURN: 0.0105367744467887
Predicted 2_DAY_RETURN: 0.0365413865855453
Predicted 7_DAY_RETURN: 2251047.0
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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 @AlasscanIsBack: @MSNBC @CNN @NBC @ABC @CBS @PBS
Don't tune in & give reality scotus show by potus any ratings
#BLACKOUTTRUMP
#BLACKOUT…
" STOCK: CBS 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: 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.
|
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: 0.0
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Predicted 1_DAY_RETURN: -0.0017027863777089
Predicted 2_DAY_RETURN: -0.0030959752321979
Predicted 7_DAY_RETURN: -0.024767801857585
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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: "RT @Themansneighbor: @Lrihendry @TrustyGordon @Starbucks I will never buy another coffee from them" 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
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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: "Starbucks" STOCK: 01/02/2017 DATE: 53.9
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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 @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
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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: "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
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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
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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
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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: "RT @Reuters: A barb at Germany puts Trump administration on collision course with EU https://t.co/LSg0Y4YoP7" 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: "Check out Aldo Nude Patent Wedges #ALDO #PlatformsWedges https://t.co/ciaUyw1z5d 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 0.0 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: 0.0 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
|
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: Japan's Rakuten CEO tweets Trump move to ban refugees makes him cry https://t.co/5xj5X9Ymor https://t.co/Z4GuKVlS9d" 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: "Check out NFL New York Giants Mens Armor II Therma Base Synthetic Pullover Hoodie Jacket #Majestic https://t.co/oSaNmaaQ5f 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 -0.33181818181818185 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: -0.33181818181818185 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: "@Starbucks take your business to the #Country you're Most Proud Of , Kick Em 2 The Curb #BoycottStarbucks #USA ✅ https://t.co/kZNGP3qLGx
" 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 0.65.
|
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: 0.65
|
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: "@Dustinpenner25 @ATT @ATTCares totally get it. We were in hell for 4 years pre wifi calling days :) https://t.co/HLAi8dv2MY" 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: "AT&T" STOCK: 01/02/2017 DATE: 42.06
|
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 @ATT.
|
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: -0.0057061340941512 2_DAY_RETURN: -0.0011887779362816 3_DAY_RETURN: -0.0159296243461721 7_DAY_RETURN: 32082528.0
|
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: 0.0023775558725628 PX_VOLUME: 14.7 VOLATILITY_10D: 15.146 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @ATT
|
Predicted 1_DAY_RETURN: -0.0057061340941512
Predicted 2_DAY_RETURN: -0.0011887779362816
Predicted 7_DAY_RETURN: 32082528.0
|
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