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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: "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
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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: 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
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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: "Imprisoned for Christ Brand: Tyndale House Publishers https://t.co/DIsXHJPDqP via @amazon #Ostracized #people" 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: "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.
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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: -0.0023667928155223 2_DAY_RETURN: 0.0041088484411605 3_DAY_RETURN: 0.0050099116958009 7_DAY_RETURN: 3850181.0
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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: 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
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Predicted 1_DAY_RETURN: -0.0023667928155223
Predicted 2_DAY_RETURN: 0.0041088484411605
Predicted 7_DAY_RETURN: 3850181.0
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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: "Check out Rare Unusual Vintage Fishing Lure Letter Opener Glass Eyes Spain Inoxidable https://t.co/WrshBHekFV 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.
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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: "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 0.25 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: 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.
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STOCK: 01/02/2017 LAST_PRICE: -0.0108763206960845 PX_VOLUME: 33.037 VOLATILITY_10D: 22.838 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.25 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: "Check out SMALL RUSSIAN ORTHODOX CROSS church Christian 925 Silver Russia SAVE AND PROTECT https://t.co/2LJ9wfhoVc 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.
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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.
|
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 -0.0625 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: 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: -0.0625 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.
|
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
|
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
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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: "RT @3cb9882c032b43e: @Awake_Today @Houston_Vicious @Starbucks and what is with your LOGO ? #PizzaGate https://t.co/gA2DNOYRI3" 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
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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: "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.
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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: 0.0371057513914656 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: "@nb182 @Starbucks I feel sad for you Your need to call ppl names. Ppl like you who feel they could hide behind their devices & say whatever" 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: "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 -0.5 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: -0.5 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: "@apoure25 @easyJet... should be useful to look at once in EU. LFSB isn't to far away either" 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: "easyJet" STOCK: 01/02/2017 DATE: 942.5
|
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 @easyJet.
|
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: 0.0217506631299734 2_DAY_RETURN: 0.0334217506631299 3_DAY_RETURN: 0.0694960212201591 7_DAY_RETURN: 4927051.0
|
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: 0.0079575596816976 PX_VOLUME: 57.302 VOLATILITY_10D: 39.921 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.3 TEXTBLOB_POLARITY: @easyJet
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Predicted 1_DAY_RETURN: 0.0217506631299734
Predicted 2_DAY_RETURN: 0.0334217506631299
Predicted 7_DAY_RETURN: 4927051.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @MarkSimoneNY: Hey @Starbucks, instead of hiring 10,000 refugees, how about hiring 10,000 veterans.
" 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 0.0.
|
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
|
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.
|
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: "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 @boiicyeu: @trvo512 @McDonalds that nigga got huge ass thumb" 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: "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 0.4000000000000001 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: 0.4000000000000001 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: "@Lrihendry @Starbucks When they demand women be allowed in their stores in the Mid-East muslim nations is when I'll go back. #hypocrites." 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: "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.
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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: 0.0244897959183673 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: "Checked out this amazing display of @Nissan #intelligentmobility concept vehicles 👏👏 #GINZA https://t.co/hLG5RQLz00" 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
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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
|
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: "Nissan" STOCK: 01/02/2017 DATE: 1112.0
|
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 0.6000000000000001 and the TextBlob polarity score is @Nissan.
|
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: 0.0211330935251798 2_DAY_RETURN: 0.0256294964028776 3_DAY_RETURN: 0.0197841726618705 7_DAY_RETURN: 14266600.0
|
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: 0.0062949640287769 PX_VOLUME: 14.996 VOLATILITY_10D: 17.915 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.6000000000000001 TEXTBLOB_POLARITY: @Nissan
|
Predicted 1_DAY_RETURN: 0.0211330935251798
Predicted 2_DAY_RETURN: 0.0256294964028776
Predicted 7_DAY_RETURN: 14266600.0
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "RT @shannoncoulter: "[W]e cherish the diverse, international workforce we have around the globe." Thank you @adidas for siding with inc…
" STOCK: adidas 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: adidas 1_DAY_RETURN: -0.007726718178121 2_DAY_RETURN: 0.0196624644164295 3_DAY_RETURN: 0.0426392842618952 7_DAY_RETURN: 0.0431001762233971
|
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: adidas LAST_PRICE: 147.54 PX_VOLUME: 813955.0 VOLATILITY_10D: 21.006 VOLATILITY_30D: 19.114 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0
|
Predicted 1_DAY_RETURN: -0.007726718178121
Predicted 2_DAY_RETURN: 0.0196624644164295
Predicted 7_DAY_RETURN: 0.0431001762233971
|
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
|
TWEET: "When will you start administering coffee enemas @Starbucks" 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 HEALTHY JAMAICAN BLUE BOMBER CAKE SOAP-MAINTAINING A DRY SKIN TONE (3)PER PACK https://t.co/BBxDmkd7hy 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 0.14444444444444446 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: 0.14444444444444446 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 @rosenbergann: Great hosting @StanfordNewYork today at @SAP @_HudsonYardsNYC & insightful hearing that the she students preferred… " 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: "SAP" STOCK: 01/02/2017 DATE: 84.194
|
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 @SAP.
|
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: 0.0138014585362378 2_DAY_RETURN: 0.011865453595268 3_DAY_RETURN: 0.0084566596194503 7_DAY_RETURN: 2344503.0
|
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: 0.0046677910539943 PX_VOLUME: 11.43 VOLATILITY_10D: 9.509 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.8 TEXTBLOB_POLARITY: @SAP
|
Predicted 1_DAY_RETURN: 0.0138014585362378
Predicted 2_DAY_RETURN: 0.011865453595268
Predicted 7_DAY_RETURN: 2344503.0
|
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 @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.
|
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