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Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN.
STOCK: 18/09/2018 LAST_PRICE: -0.0062376297007137 PX_VOLUME: 16.992 VOLATILITY_10D: 16.753 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Google
Predicted 1_DAY_RETURN: 0.0093136036877416 Predicted 2_DAY_RETURN: 0.0093136036877416 Predicted 7_DAY_RETURN: 1615701.0
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! πŸ‘‘" 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! πŸ‘‘" 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! πŸ‘‘" 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! πŸ‘‘" 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: "@Walmart Walmart, why not just have the Waltons donate instead of your underpaid associates and your customers? Sh… https://t.co/oRgnUEIfew " STOCK: Walmart 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: Walmart 1_DAY_RETURN: -0.006392119878445 2_DAY_RETURN: -0.0088022634391701 3_DAY_RETURN: -0.0088022634391701 7_DAY_RETURN: 0.0126794509064234
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: Walmart LAST_PRICE: 95.43 PX_VOLUME: 6760152.0 VOLATILITY_10D: 10.875 VOLATILITY_30D: 30.164 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0
Predicted 1_DAY_RETURN: -0.006392119878445 Predicted 2_DAY_RETURN: -0.0088022634391701 Predicted 7_DAY_RETURN: 0.0126794509064234
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @SAP: SAP technology allows @elephantsrhinos (ERP) to monitor elephants and rhinos with drones and sensors to reduce poaching. https://t…" 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: 18/09/2018 DATE: 103.02
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 @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: 18/09/2018 1_DAY_RETURN: 0.0120364977674238 2_DAY_RETURN: 0.0120364977674238 3_DAY_RETURN: -0.0033003300330031 7_DAY_RETURN: 2179139.0
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: -0.005629974762182 PX_VOLUME: 16.25 VOLATILITY_10D: 17.292 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @SAP
Predicted 1_DAY_RETURN: 0.0120364977674238 Predicted 2_DAY_RETURN: 0.0120364977674238 Predicted 7_DAY_RETURN: 2179139.0
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 Playstation 2 Sony PS2 Console Only Video Game System Model - TESTED - Great #Sony https://t.co/8jlXP0MkjZ 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: "Sony" STOCK: 18/09/2018 DATE: 6652.0
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 0.13333333333333333 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: -0.0033072760072158 2_DAY_RETURN: -0.0033072760072158 3_DAY_RETURN: -0.0476548406494287 7_DAY_RETURN: 6892000.0
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: -0.0033072760072158 PX_VOLUME: 21.509 VOLATILITY_10D: 20.164 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.13333333333333333 TEXTBLOB_POLARITY: @eBay
Predicted 1_DAY_RETURN: -0.0033072760072158 Predicted 2_DAY_RETURN: -0.0033072760072158 Predicted 7_DAY_RETURN: 6892000.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "RT @People4Bernie: HAPPENING NOW: McDonald's workers just went on the first-ever national strike against sexual harassment. @McDonalds: Me… " STOCK: McDonald's 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 0.5.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: McDonald's 1_DAY_RETURN: 0.0023451860302971 2_DAY_RETURN: 0.0194587057108448 3_DAY_RETURN: 0.0194587057108448 7_DAY_RETURN: 0.0434176332636115
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: McDonald's LAST_PRICE: 157.77 PX_VOLUME: 3722864.0 VOLATILITY_10D: 13.121 VOLATILITY_30D: 13.1 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.5
Predicted 1_DAY_RETURN: 0.0023451860302971 Predicted 2_DAY_RETURN: 0.0194587057108448 Predicted 7_DAY_RETURN: 0.0434176332636115
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! πŸ‘‘" 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! πŸ‘‘" 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! πŸ‘‘" 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! πŸ‘‘" 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 Womens Next Jacket Size 10 https://t.co/3oKm1uLuDk @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: "Next" STOCK: 18/09/2018 DATE: 5340.0
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 0.0 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: 0.0018726591760299 2_DAY_RETURN: 0.0018726591760299 3_DAY_RETURN: 0.0157303370786516 7_DAY_RETURN: 476980.0
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: 0.0059925093632958 PX_VOLUME: 11.929 VOLATILITY_10D: 14.738 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay
Predicted 1_DAY_RETURN: 0.0018726591760299 Predicted 2_DAY_RETURN: 0.0018726591760299 Predicted 7_DAY_RETURN: 476980.0
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! πŸ‘‘" 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: "@kelss_nicole14 @pepsi Get outta here!!! You don't even like Pepsi 😀" 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 @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: 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: @pepsi
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: "@MCU_Tweets @Disney Take all my money...just take it Disney." 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: 19/09/2018 DATE: 109.79
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Disney.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
STOCK: 19/09/2018 1_DAY_RETURN: -0.003916567993442 2_DAY_RETURN: -0.0048273977593587 3_DAY_RETURN: -0.0030057382275253 7_DAY_RETURN: 5964771.0
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: 19/09/2018 LAST_PRICE: -0.0023681573913835 PX_VOLUME: 11.93 VOLATILITY_10D: 9.265 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Disney
Predicted 1_DAY_RETURN: -0.003916567993442 Predicted 2_DAY_RETURN: -0.0048273977593587 Predicted 7_DAY_RETURN: 5964771.0
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! πŸ‘‘" 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: 19/09/2018 DATE: 55.43
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: 19/09/2018 1_DAY_RETURN: -0.0155150640447411 2_DAY_RETURN: -0.0122677250586325 3_DAY_RETURN: -0.008298755186722 7_DAY_RETURN: 7451644.0
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: 19/09/2018 LAST_PRICE: -0.0064946779722172 PX_VOLUME: 9.032 VOLATILITY_10D: 11.19 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Starbucks
Predicted 1_DAY_RETURN: -0.0155150640447411 Predicted 2_DAY_RETURN: -0.0122677250586325 Predicted 7_DAY_RETURN: 7451644.0
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned.
TWEET: "Just saw this on Amazon: VideoSecu 2 Heavy duty PA DJ Club Adjustabl... by VideoSecu for $39.89 https://t.co/QO7XFMKDch via @amazon" STOCK: nan DATE: nan
Sentiment: (Provide sentiment here) Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan.
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends.
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