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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: 27/09/2018 1_DAY_RETURN: -0.0296288513566756 2_DAY_RETURN: -0.0291560505371541 3_DAY_RETURN: -0.0403194032202988 7_DAY_RETURN: 7326246.0 | 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: 27/09/2018 LAST_PRICE: -0.0074334795513645 PX_VOLUME: 40.101 VOLATILITY_10D: 40.226 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: -0.0296288513566756
Predicted 2_DAY_RETURN: -0.0291560505371541
Predicted 7_DAY_RETURN: 7326246.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@PlanetFord59 @Ford We bought a Ford Explorer 2011 last year during the aftermath of Harvey. We purchased my car a… https://t.co/K1kA49TI6A" 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: 27/09/2018 DATE: 9.23 | 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 @Ford. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 27/09/2018 1_DAY_RETURN: 0.0173347778981581 2_DAY_RETURN: 0.0390032502708558 3_DAY_RETURN: 0.0628385698808234 7_DAY_RETURN: 57272192.0 | 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: 27/09/2018 LAST_PRICE: 0.0043336944745394 PX_VOLUME: 24.558000000000003 VOLATILITY_10D: 23.023000000000003 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Ford | Predicted 1_DAY_RETURN: 0.0173347778981581
Predicted 2_DAY_RETURN: 0.0390032502708558
Predicted 7_DAY_RETURN: 57272192.0 |
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: Ford Motor Chief Executive Officer James Hackett said that metals tariffs are costing the carmaker $1 billion. https://t.co/Uz…" 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: 27/09/2018 DATE: 9.23 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Reuters. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 27/09/2018 1_DAY_RETURN: 0.0173347778981581 2_DAY_RETURN: 0.0390032502708558 3_DAY_RETURN: 0.0628385698808234 7_DAY_RETURN: 57272192.0 | 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: 27/09/2018 LAST_PRICE: 0.0043336944745394 PX_VOLUME: 24.558000000000003 VOLATILITY_10D: 23.023000000000003 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0173347778981581
Predicted 2_DAY_RETURN: 0.0390032502708558
Predicted 7_DAY_RETURN: 57272192.0 |
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: Japanese Style Otamtone Japan by Maywa Denk... by Cube for $22.89 https://t.co/kzxvD5A2HZ @amazon 님이 공유" 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: "Amazon" STOCK: 27/09/2018 DATE: 2012.98 | 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 @amazon. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 27/09/2018 1_DAY_RETURN: -0.0190910987689892 2_DAY_RETURN: -0.0390565231646614 3_DAY_RETURN: -0.0341185704776004 7_DAY_RETURN: 4329391.0 | 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: 27/09/2018 LAST_PRICE: -0.0189420659917138 PX_VOLUME: 28.695 VOLATILITY_10D: 22.88300000000001 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0190910987689892
Predicted 2_DAY_RETURN: -0.0390565231646614
Predicted 7_DAY_RETURN: 4329391.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Google: Turning back, flipping forward: how we’re marking 20(ish) years of Google this month → https://t.co/bxzOlsDTma https://t.co/voo…
" STOCK: Google DATE: 27/09/2018 | 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: Google 1_DAY_RETURN: -0.0110157699443413 2_DAY_RETURN: -0.0111565730188177 3_DAY_RETURN: -0.0230254439438112 7_DAY_RETURN: -0.013078120858733 | 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: Google LAST_PRICE: 1207.36 PX_VOLUME: 1813652.0 VOLATILITY_10D: 18.416 VOLATILITY_30D: 17.695 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0110157699443413
Predicted 2_DAY_RETURN: -0.0111565730188177
Predicted 7_DAY_RETURN: -0.013078120858733 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "3. So once the Apple rep gets the @UPS sup on the phone, things take a turn for the "better". Wait, have they reall… https://t.co/l4fmCt9O8F
" STOCK: Apple DATE: 27/09/2018 | 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: -0.020137808401867 2_DAY_RETURN: -0.0122693931984885 3_DAY_RETURN: -0.0184929984440986 7_DAY_RETURN: -0.0218715270060012 | The stock shows a consistent negative return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Apple LAST_PRICE: 224.95 PX_VOLUME: 30181227.0 VOLATILITY_10D: 22.98 VOLATILITY_30D: 20.811 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.020137808401867
Predicted 2_DAY_RETURN: -0.0122693931984885
Predicted 7_DAY_RETURN: -0.0218715270060012 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@lifeatgoogle Google Pixel Fraud might happen again with the launch of Pixel 3 on 9 October 2018
@Google is Killin… https://t.co/icOG5hmUBC
" STOCK: Google DATE: 27/09/2018 | 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: Google 1_DAY_RETURN: -0.0110157699443413 2_DAY_RETURN: -0.0111565730188177 3_DAY_RETURN: -0.0230254439438112 7_DAY_RETURN: -0.013078120858733 | 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: Google LAST_PRICE: 1207.36 PX_VOLUME: 1813652.0 VOLATILITY_10D: 18.416 VOLATILITY_30D: 17.695 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0110157699443413
Predicted 2_DAY_RETURN: -0.0111565730188177
Predicted 7_DAY_RETURN: -0.013078120858733 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @MSFTnews: Using Microsoft #AI and the #cloud, @Shell is increasing #safety at gas stations to spot risks at the pump, like smoking, to…
" STOCK: Microsoft DATE: 27/09/2018 | 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: Microsoft 1_DAY_RETURN: -0.0037584127261602 2_DAY_RETURN: 0.00034961978848 3_DAY_RETURN: 0.0022725286251202 7_DAY_RETURN: -0.0073420155580806 | 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: Microsoft LAST_PRICE: 114.41 PX_VOLUME: 19091299.0 VOLATILITY_10D: 15.51 VOLATILITY_30D: 16.136 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0037584127261602
Predicted 2_DAY_RETURN: 0.00034961978848
Predicted 7_DAY_RETURN: -0.0073420155580806 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@businessinsider Google Pixel Fraud might happen again with the launch of Pixel 3 on 9 October 2018
@Google is Kil… https://t.co/yfExz40S4U
" STOCK: Google DATE: 27/09/2018 | 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: Google 1_DAY_RETURN: -0.0110157699443413 2_DAY_RETURN: -0.0111565730188177 3_DAY_RETURN: -0.0230254439438112 7_DAY_RETURN: -0.013078120858733 | 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: Google LAST_PRICE: 1207.36 PX_VOLUME: 1813652.0 VOLATILITY_10D: 18.416 VOLATILITY_30D: 17.695 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0110157699443413
Predicted 2_DAY_RETURN: -0.0111565730188177
Predicted 7_DAY_RETURN: -0.013078120858733 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "All-New Fire 7 Kids Edition - Amazon Official Site - The #1 kids’ https://t.co/flHuSLYqFd @amazon https://t.co/o834VuDQuO" 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: "Amazon" STOCK: 27/09/2018 DATE: 2012.98 | 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 @amazon. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 27/09/2018 1_DAY_RETURN: -0.0190910987689892 2_DAY_RETURN: -0.0390565231646614 3_DAY_RETURN: -0.0341185704776004 7_DAY_RETURN: 4329391.0 | 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: 27/09/2018 LAST_PRICE: -0.0189420659917138 PX_VOLUME: 28.695 VOLATILITY_10D: 22.88300000000001 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @amazon | Predicted 1_DAY_RETURN: -0.0190910987689892
Predicted 2_DAY_RETURN: -0.0390565231646614
Predicted 7_DAY_RETURN: 4329391.0 |
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: Ford Motor Chief Executive Officer James Hackett said that metals tariffs are costing the carmaker $1 billion. https://t.co/Uz…" 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: 27/09/2018 DATE: 9.23 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Reuters. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 27/09/2018 1_DAY_RETURN: 0.0173347778981581 2_DAY_RETURN: 0.0390032502708558 3_DAY_RETURN: 0.0628385698808234 7_DAY_RETURN: 57272192.0 | 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: 27/09/2018 LAST_PRICE: 0.0043336944745394 PX_VOLUME: 24.558000000000003 VOLATILITY_10D: 23.023000000000003 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0173347778981581
Predicted 2_DAY_RETURN: 0.0390032502708558
Predicted 7_DAY_RETURN: 57272192.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @salesforce: What will the @Apple and @Salesforce partnership look like? Join us for a live conversation with Apple VP of Product Market…" 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: "Apple" STOCK: 27/09/2018 DATE: 224.95 | 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 @Apple. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 27/09/2018 1_DAY_RETURN: -0.0122693931984885 2_DAY_RETURN: -0.0184929984440986 3_DAY_RETURN: -0.0218715270060012 7_DAY_RETURN: 30181227.0 | 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: 27/09/2018 LAST_PRICE: -0.020137808401867 PX_VOLUME: 22.98 VOLATILITY_10D: 20.811 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Apple | Predicted 1_DAY_RETURN: -0.0122693931984885
Predicted 2_DAY_RETURN: -0.0184929984440986
Predicted 7_DAY_RETURN: 30181227.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Happy birthday @Google! Google Doodle celebrates 20th birthday of the search engine https://t.co/E2f8XQ25n7" 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: 27/09/2018 DATE: 1207.36 | 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 1.0 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: 27/09/2018 1_DAY_RETURN: -0.0111565730188177 2_DAY_RETURN: -0.0230254439438112 3_DAY_RETURN: -0.013078120858733 7_DAY_RETURN: 1813652.0 | 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: 27/09/2018 LAST_PRICE: -0.0110157699443413 PX_VOLUME: 18.416 VOLATILITY_10D: 17.695 VOLATILITY_30D: 1.0 LSTM_POLARITY: 1.0 TEXTBLOB_POLARITY: @Google | Predicted 1_DAY_RETURN: -0.0111565730188177
Predicted 2_DAY_RETURN: -0.0230254439438112
Predicted 7_DAY_RETURN: 1813652.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@mmromine @McDonalds @tacobell @Wendys Ubereats does McDonald's now" 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: 27/09/2018 DATE: 166.53 | 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 @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: 27/09/2018 1_DAY_RETURN: -0.0007205908845253 2_DAY_RETURN: -0.0193358554014291 3_DAY_RETURN: -0.0344682639764607 7_DAY_RETURN: 2390670.0 | 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: 27/09/2018 LAST_PRICE: -0.0046237915090374 PX_VOLUME: 23.091 VOLATILITY_10D: 15.380999999999998 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @McDonalds | Predicted 1_DAY_RETURN: -0.0007205908845253
Predicted 2_DAY_RETURN: -0.0193358554014291
Predicted 7_DAY_RETURN: 2390670.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @ashwinravi99: Happy 20th Birthday to Dear @Google. Google personifies everything that I require in my day to day life, has definitely m…
" STOCK: Google DATE: 27/09/2018 | 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 0.4. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Google 1_DAY_RETURN: -0.0110157699443413 2_DAY_RETURN: -0.0111565730188177 3_DAY_RETURN: -0.0230254439438112 7_DAY_RETURN: -0.013078120858733 | 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: Google LAST_PRICE: 1207.36 PX_VOLUME: 1813652.0 VOLATILITY_10D: 18.416 VOLATILITY_30D: 17.695 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.4 | Predicted 1_DAY_RETURN: -0.0110157699443413
Predicted 2_DAY_RETURN: -0.0111565730188177
Predicted 7_DAY_RETURN: -0.013078120858733 |
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 conn…
" STOCK: Apple DATE: 27/09/2018 | 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: -0.020137808401867 2_DAY_RETURN: -0.0122693931984885 3_DAY_RETURN: -0.0184929984440986 7_DAY_RETURN: -0.0218715270060012 | The stock shows a consistent negative return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: Apple LAST_PRICE: 224.95 PX_VOLUME: 30181227.0 VOLATILITY_10D: 22.98 VOLATILITY_30D: 20.811 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.020137808401867
Predicted 2_DAY_RETURN: -0.0122693931984885
Predicted 7_DAY_RETURN: -0.0218715270060012 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@joele__ @Google Google won't share your private info. because google is THE ADVERTISER" 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: 27/09/2018 DATE: 1207.36 | 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: 27/09/2018 1_DAY_RETURN: -0.0111565730188177 2_DAY_RETURN: -0.0230254439438112 3_DAY_RETURN: -0.013078120858733 7_DAY_RETURN: 1813652.0 | 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: 27/09/2018 LAST_PRICE: -0.0110157699443413 PX_VOLUME: 18.416 VOLATILITY_10D: 17.695 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Google | Predicted 1_DAY_RETURN: -0.0111565730188177
Predicted 2_DAY_RETURN: -0.0230254439438112
Predicted 7_DAY_RETURN: 1813652.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Cocoa_Bean10: @Reuters 👏🏻Att Reuters: Here’s another allegation! Based on the vetting and reporting of gossip (not facts) you’ve been d…" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Reuters" STOCK: 27/09/2018 DATE: 50.358000000000004 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Reuters. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 27/09/2018 1_DAY_RETURN: -0.0004388577783073 2_DAY_RETURN: -0.0061241510782796 3_DAY_RETURN: -0.0045931133087097 7_DAY_RETURN: 4572793.0 | 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: 27/09/2018 LAST_PRICE: -0.005905715080027 PX_VOLUME: 6.807 VOLATILITY_10D: 12.842 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: -0.0004388577783073
Predicted 2_DAY_RETURN: -0.0061241510782796
Predicted 7_DAY_RETURN: 4572793.0 |
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: Ford Motor Chief Executive Officer James Hackett said that metals tariffs are costing the carmaker $1 billion. https://t.co/Uz…" 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: 27/09/2018 DATE: 9.23 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @Reuters. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 27/09/2018 1_DAY_RETURN: 0.0173347778981581 2_DAY_RETURN: 0.0390032502708558 3_DAY_RETURN: 0.0628385698808234 7_DAY_RETURN: 57272192.0 | 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: 27/09/2018 LAST_PRICE: 0.0043336944745394 PX_VOLUME: 24.558000000000003 VOLATILITY_10D: 23.023000000000003 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Reuters | Predicted 1_DAY_RETURN: 0.0173347778981581
Predicted 2_DAY_RETURN: 0.0390032502708558
Predicted 7_DAY_RETURN: 57272192.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Happy 20th Birthday to Dear
@Google
. Google personifies everything that I require in my day to day life, has defi… https://t.co/JNZP4Cc3gp
" STOCK: Google DATE: 27/09/2018 | 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 0.4. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: Google 1_DAY_RETURN: -0.0110157699443413 2_DAY_RETURN: -0.0111565730188177 3_DAY_RETURN: -0.0230254439438112 7_DAY_RETURN: -0.013078120858733 | 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: Google LAST_PRICE: 1207.36 PX_VOLUME: 1813652.0 VOLATILITY_10D: 18.416 VOLATILITY_30D: 17.695 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.4 | Predicted 1_DAY_RETURN: -0.0110157699443413
Predicted 2_DAY_RETURN: -0.0111565730188177
Predicted 7_DAY_RETURN: -0.013078120858733 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "@Reuters Dr. Christine Ford has a name, Reuters.
" STOCK: Ford DATE: 27/09/2018 | 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: Ford 1_DAY_RETURN: 0.0043336944745394 2_DAY_RETURN: 0.0173347778981581 3_DAY_RETURN: 0.0390032502708558 7_DAY_RETURN: 0.0628385698808234 | 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: Ford LAST_PRICE: 9.23 PX_VOLUME: 57272192.0 VOLATILITY_10D: 24.558000000000003 VOLATILITY_30D: 23.023000000000003 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: 0.0043336944745394
Predicted 2_DAY_RETURN: 0.0173347778981581
Predicted 7_DAY_RETURN: 0.0628385698808234 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Mastercard: Ever think you’d get to go on a dream trip just for buying 🍕? That’s what happened to John when he used his Mastercard! Use…" 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: "Mastercard" STOCK: 27/09/2018 DATE: 222.31 | 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 @Mastercard. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 27/09/2018 1_DAY_RETURN: -0.0008546624083486 2_DAY_RETURN: -0.0043182942737619 3_DAY_RETURN: -0.0041383653456885 7_DAY_RETURN: 2645186.0 | The stock shows a consistent positive return trend over the specified periods. |
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