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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: 18/09/2018 1_DAY_RETURN: -0.0058107862720174 2_DAY_RETURN: -0.0058107862720174 3_DAY_RETURN: 0.0009079353550026 7_DAY_RETURN: 7569586.0
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: 18/09/2018 LAST_PRICE: -0.0090793535500272 PX_VOLUME: 9.239 VOLATILITY_10D: 11.723 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks
Predicted 1_DAY_RETURN: -0.0058107862720174 Predicted 2_DAY_RETURN: -0.0058107862720174 Predicted 7_DAY_RETURN: 7569586.0
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 Disney Exclusive Retired Eeyore In Flower Bed Cookie Jar Winnie the Pooh https://t.co/cTUsbmhgSD @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: "Disney" STOCK: 18/09/2018 DATE: 109.53
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: 18/09/2018 1_DAY_RETURN: -0.0024650780608052 2_DAY_RETURN: -0.0024650780608052 3_DAY_RETURN: 0.0006390943120605 7_DAY_RETURN: 4937821.0
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: 18/09/2018 LAST_PRICE: -0.0015520861864329 PX_VOLUME: 12.037 VOLATILITY_10D: 11.133 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay
Predicted 1_DAY_RETURN: -0.0024650780608052 Predicted 2_DAY_RETURN: -0.0024650780608052 Predicted 7_DAY_RETURN: 4937821.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Michaelfulton45: @JayGalxby The whole show needs to be on Netflix now @netflix" 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: "Netflix" STOCK: 18/09/2018 DATE: 367.65
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 @netflix.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 18/09/2018 1_DAY_RETURN: -0.0084047327621378 2_DAY_RETURN: -0.0084047327621378 3_DAY_RETURN: -0.0318781449748401 7_DAY_RETURN: 10413981.0
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: 18/09/2018 LAST_PRICE: -0.0470556235550114 PX_VOLUME: 42.772 VOLATILITY_10D: 41.89 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.2 TEXTBLOB_POLARITY: @netflix
Predicted 1_DAY_RETURN: -0.0084047327621378 Predicted 2_DAY_RETURN: -0.0084047327621378 Predicted 7_DAY_RETURN: 10413981.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Cisco: Meetings are a critical part of how we work today. Here's how Cisco is making #meetings better with easier scheduling, new video… " STOCK: Cisco DATE: 18/09/2018
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: Cisco 1_DAY_RETURN: -0.0073746312684366 2_DAY_RETURN: -0.0012642225031606 3_DAY_RETURN: -0.0012642225031606 7_DAY_RETURN: -0.0090602612726506
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: Cisco LAST_PRICE: 47.46 PX_VOLUME: 16469562.0 VOLATILITY_10D: 7.879 VOLATILITY_30D: 13.158 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: -0.0073746312684366 Predicted 2_DAY_RETURN: -0.0012642225031606 Predicted 7_DAY_RETURN: -0.0090602612726506
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @jilbijou45: Check out Mickey Mouse Disney Store size 6-12 M Plush One Piece Halloween Costume Suit https://t.co/bwwU0R8pfh 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: "Disney" STOCK: 18/09/2018 DATE: 109.53
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: 18/09/2018 1_DAY_RETURN: -0.0024650780608052 2_DAY_RETURN: -0.0024650780608052 3_DAY_RETURN: 0.0006390943120605 7_DAY_RETURN: 4937821.0
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: 18/09/2018 LAST_PRICE: -0.0015520861864329 PX_VOLUME: 12.037 VOLATILITY_10D: 11.133 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay
Predicted 1_DAY_RETURN: -0.0024650780608052 Predicted 2_DAY_RETURN: -0.0024650780608052 Predicted 7_DAY_RETURN: 4937821.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "@BlaugranaHome @Nike First thing that came to mind was "Did these Nike guys just copy and paste this assignment? " " STOCK: Nike DATE: 18/09/2018
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 1 and the TextBlob polarity score is 0.25.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: Nike 1_DAY_RETURN: -0.0234576589256392 2_DAY_RETURN: -0.0207600281491908 3_DAY_RETURN: -0.0207600281491908 7_DAY_RETURN: -0.0308468214872156
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: Nike LAST_PRICE: 85.26 PX_VOLUME: 7277700.0 VOLATILITY_10D: 15.386 VOLATILITY_30D: 18.916 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.25
Predicted 1_DAY_RETURN: -0.0234576589256392 Predicted 2_DAY_RETURN: -0.0207600281491908 Predicted 7_DAY_RETURN: -0.0308468214872156
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @UPS: UPS to hire 100,000 people for the Holiday Season https://t.co/4XXnC32lNT " STOCK: UPS DATE: 18/09/2018
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: UPS 1_DAY_RETURN: 0.0071887686062247 2_DAY_RETURN: 0.0181833558863329 3_DAY_RETURN: 0.0181833558863329 7_DAY_RETURN: 0.0408491204330175
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: UPS LAST_PRICE: 118.24 PX_VOLUME: 2851420.0 VOLATILITY_10D: 18.827 VOLATILITY_30D: 15.242 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: 0.0071887686062247 Predicted 2_DAY_RETURN: 0.0181833558863329 Predicted 7_DAY_RETURN: 0.0408491204330175
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Apple: Introducing Apple Watch Series 4. Fundamentally redesigned and re-engineered to help you stay even more active, healthy, and con… " STOCK: Apple DATE: 18/09/2018
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: -0.0016495601173021 2_DAY_RETURN: 0.0256598240469208 3_DAY_RETURN: 0.0256598240469208 7_DAY_RETURN: 0.0257056451612902
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: Apple LAST_PRICE: 218.24 PX_VOLUME: 31571712.0 VOLATILITY_10D: 28.915 VOLATILITY_30D: 19.63 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: -0.0016495601173021 Predicted 2_DAY_RETURN: 0.0256598240469208 Predicted 7_DAY_RETURN: 0.0257056451612902
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 Gift Ideas (for the beginner) on Amazon! https://t.co/f8COV15AMx via @amazon " STOCK: Amazon DATE: 18/09/2018
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: Amazon 1_DAY_RETURN: -0.0170114113495273 2_DAY_RETURN: 0.0150124932381958 3_DAY_RETURN: 0.0150124932381958 7_DAY_RETURN: 0.0237500321990675
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: Amazon LAST_PRICE: 1941.05 PX_VOLUME: 4268706.0 VOLATILITY_10D: 27.565 VOLATILITY_30D: 22.124 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: -0.0170114113495273 Predicted 2_DAY_RETURN: 0.0150124932381958 Predicted 7_DAY_RETURN: 0.0237500321990675
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "@Wendys @CocaCola What about a whopper and a Pepsi @McDonalds @Wendys" 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: "Pepsi" STOCK: 18/09/2018 DATE: 113.98
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 @CocaCola.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 18/09/2018 1_DAY_RETURN: 0.0051763467274959 2_DAY_RETURN: 0.0051763467274959 3_DAY_RETURN: -0.0057027548692753 7_DAY_RETURN: 4081437.0
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: 18/09/2018 LAST_PRICE: 0.0124583260221091 PX_VOLUME: 12.057 VOLATILITY_10D: 12.047 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @CocaCola
Predicted 1_DAY_RETURN: 0.0051763467274959 Predicted 2_DAY_RETURN: 0.0051763467274959 Predicted 7_DAY_RETURN: 4081437.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @Bondkels: You don't want to be caught wearing Nike and then you do this. I love @Nike ✔✔✔✔✔ https://t.co/FSpuie0bHn" 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: "Nike" STOCK: 18/09/2018 DATE: 85.26
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 @Nike.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 18/09/2018 1_DAY_RETURN: -0.0207600281491908 2_DAY_RETURN: -0.0207600281491908 3_DAY_RETURN: -0.0308468214872156 7_DAY_RETURN: 7277700.0
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: 18/09/2018 LAST_PRICE: -0.0234576589256392 PX_VOLUME: 15.386 VOLATILITY_10D: 18.916 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Nike
Predicted 1_DAY_RETURN: -0.0207600281491908 Predicted 2_DAY_RETURN: -0.0207600281491908 Predicted 7_DAY_RETURN: 7277700.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "#NationalCheeseburgerDay Time to go to McDonald's to buy a cheeseburger. @McDonalds" 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: 18/09/2018 DATE: 157.77
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 @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: 18/09/2018 1_DAY_RETURN: 0.0194587057108448 2_DAY_RETURN: 0.0194587057108448 3_DAY_RETURN: 0.0434176332636115 7_DAY_RETURN: 3722864.0
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: 18/09/2018 LAST_PRICE: 0.0023451860302971 PX_VOLUME: 13.121 VOLATILITY_10D: 13.1 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @McDonalds
Predicted 1_DAY_RETURN: 0.0194587057108448 Predicted 2_DAY_RETURN: 0.0194587057108448 Predicted 7_DAY_RETURN: 3722864.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @jwjnational: McDonald's workers are taking action today in the first-ever national strike against sexual harassment. @McDonalds: Meet w…" 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: 18/09/2018 DATE: 157.77
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: 18/09/2018 1_DAY_RETURN: 0.0194587057108448 2_DAY_RETURN: 0.0194587057108448 3_DAY_RETURN: 0.0434176332636115 7_DAY_RETURN: 3722864.0
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: 18/09/2018 LAST_PRICE: 0.0023451860302971 PX_VOLUME: 13.121 VOLATILITY_10D: 13.1 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.3 TEXTBLOB_POLARITY: @McDonalds
Predicted 1_DAY_RETURN: 0.0194587057108448 Predicted 2_DAY_RETURN: 0.0194587057108448 Predicted 7_DAY_RETURN: 3722864.0
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: Netflix and HBO tie for total Emmy wins https://t.co/PR5p7Uznx4 via @ReutersTV https://t.co/9TptfXLieO" 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: "Netflix" STOCK: 18/09/2018 DATE: 367.65
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 0.15 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: 18/09/2018 1_DAY_RETURN: -0.0084047327621378 2_DAY_RETURN: -0.0084047327621378 3_DAY_RETURN: -0.0318781449748401 7_DAY_RETURN: 10413981.0
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: 18/09/2018 LAST_PRICE: -0.0470556235550114 PX_VOLUME: 42.772 VOLATILITY_10D: 41.89 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.15 TEXTBLOB_POLARITY: @Reuters
Predicted 1_DAY_RETURN: -0.0084047327621378 Predicted 2_DAY_RETURN: -0.0084047327621378 Predicted 7_DAY_RETURN: 10413981.0
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: @chocohyoo Hyungwon will always be our Starbucks king! 👑" 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: 18/09/2018 DATE: 55.07
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: 18/09/2018 1_DAY_RETURN: -0.0058107862720174 2_DAY_RETURN: -0.0058107862720174 3_DAY_RETURN: 0.0009079353550026 7_DAY_RETURN: 7569586.0
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: 18/09/2018 LAST_PRICE: -0.0090793535500272 PX_VOLUME: 9.239 VOLATILITY_10D: 11.723 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks
Predicted 1_DAY_RETURN: -0.0058107862720174 Predicted 2_DAY_RETURN: -0.0058107862720174 Predicted 7_DAY_RETURN: 7569586.0
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: @chocohyoo Hyungwon will always be our Starbucks king! 👑" 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: 18/09/2018 DATE: 55.07
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: 18/09/2018 1_DAY_RETURN: -0.0058107862720174 2_DAY_RETURN: -0.0058107862720174 3_DAY_RETURN: 0.0009079353550026 7_DAY_RETURN: 7569586.0
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: 18/09/2018 LAST_PRICE: -0.0090793535500272 PX_VOLUME: 9.239 VOLATILITY_10D: 11.723 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks
Predicted 1_DAY_RETURN: -0.0058107862720174 Predicted 2_DAY_RETURN: -0.0058107862720174 Predicted 7_DAY_RETURN: 7569586.0
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: @chocohyoo Hyungwon will always be our Starbucks king! 👑" 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: 18/09/2018 DATE: 55.07
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: 18/09/2018 1_DAY_RETURN: -0.0058107862720174 2_DAY_RETURN: -0.0058107862720174 3_DAY_RETURN: 0.0009079353550026 7_DAY_RETURN: 7569586.0
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: 18/09/2018 LAST_PRICE: -0.0090793535500272 PX_VOLUME: 9.239 VOLATILITY_10D: 11.723 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks
Predicted 1_DAY_RETURN: -0.0058107862720174 Predicted 2_DAY_RETURN: -0.0058107862720174 Predicted 7_DAY_RETURN: 7569586.0
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: @chocohyoo Hyungwon will always be our Starbucks king! 👑" 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: 18/09/2018 DATE: 55.07
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: 18/09/2018 1_DAY_RETURN: -0.0058107862720174 2_DAY_RETURN: -0.0058107862720174 3_DAY_RETURN: 0.0009079353550026 7_DAY_RETURN: 7569586.0
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: 18/09/2018 LAST_PRICE: -0.0090793535500272 PX_VOLUME: 9.239 VOLATILITY_10D: 11.723 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks
Predicted 1_DAY_RETURN: -0.0058107862720174 Predicted 2_DAY_RETURN: -0.0058107862720174 Predicted 7_DAY_RETURN: 7569586.0
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 99-03 Ford Diesel XC3F-12B599-AC IDM Injector Driver Control Module #Ford https://t.co/AlgVElxTaj 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: "Ford" STOCK: 18/09/2018 DATE: 9.58
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: 18/09/2018 1_DAY_RETURN: -0.0135699373695199 2_DAY_RETURN: -0.0135699373695199 3_DAY_RETURN: -0.0281837160751565 7_DAY_RETURN: 57055398.0
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: 18/09/2018 LAST_PRICE: -0.0031315240083506 PX_VOLUME: 15.424 VOLATILITY_10D: 22.174 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay
Predicted 1_DAY_RETURN: -0.0135699373695199 Predicted 2_DAY_RETURN: -0.0135699373695199 Predicted 7_DAY_RETURN: 57055398.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "@Google @arai @amazon Google helmet with google home enabled? Or a helmet that's Alexa enabled?? @JeffBezos… https://t.co/ph9F1PbrWl" 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: "Google" STOCK: 18/09/2018 DATE: 1167.11
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: 18/09/2018 1_DAY_RETURN: 0.0093136036877416 2_DAY_RETURN: 0.0093136036877416 3_DAY_RETURN: 0.0196039790593861 7_DAY_RETURN: 1615701.0
The stock shows a consistent positive return trend over the specified periods.