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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! π" 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! π" 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! π" 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! π" 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://tβ¦" 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: Meβ¦
" 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! π" 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! π" 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! π" 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! π" 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! π" 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 π€" 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! π" 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 |
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