instruction
stringclasses 3
values | input
stringlengths 33
307
| output
stringlengths 66
248
|
|---|---|---|
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: Senate hearing with Christine Blasey Ford, who accused Supreme Court nominee Kavanaugh of sexual assault, continues https://t.…
" 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 0.5. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 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: 0.5 | 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: "Dr. Ford and I both run on @CocaCola #IBelieveHer https://t.co/EzwBQNJ3iI" 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 @CocaCola. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 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: @CocaCola | 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: "@alexanderbruz @mark_suiter @Google You live in Palo Alto? We have a gazillion students and Google employees." 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 0.13636363636363635 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: 0.13636363636363635 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 @oOo_bubbles: I'm a Pepsi girl but I'm switching to @CocaCola. #Strongwomen drink it. #KavanaughHearings #ChristineBlaseyFord #metoo htt…" 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: 27/09/2018 DATE: 111.05 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.0 and the TextBlob polarity score is @CocaCola. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 27/09/2018 1_DAY_RETURN: 0.0082845565060783 2_DAY_RETURN: 0.0109860423232777 3_DAY_RETURN: 0.0375506528590724 7_DAY_RETURN: 3841618.0 | 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: 0.0040522287257992 PX_VOLUME: 16.618 VOLATILITY_10D: 14.058 VOLATILITY_30D: -1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @CocaCola | Predicted 1_DAY_RETURN: 0.0082845565060783
Predicted 2_DAY_RETURN: 0.0109860423232777
Predicted 7_DAY_RETURN: 3841618.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @Ebolahitmehard: Hi when are you going to put the spooky shit on Netflix @netflix" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Netflix" STOCK: 27/09/2018 DATE: 380.71 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is -0.2 and the TextBlob polarity score is @netflix. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: 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: -0.2 TEXTBLOB_POLARITY: @netflix | 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: "RT @HungryTrucker: One of the tricks @facebook does is track your movements. I never told Facebook where I work but they obviously figured…" 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: "Facebook" STOCK: 27/09/2018 DATE: 168.84 | 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 @facebook. |
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: -0.0232764747690121 2_DAY_RETURN: -0.0203150912106136 3_DAY_RETURN: -0.0167022032693674 7_DAY_RETURN: 27266856.0 | 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: -0.0111940298507463 PX_VOLUME: 21.559 VOLATILITY_10D: 21.896 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @facebook | Predicted 1_DAY_RETURN: -0.0232764747690121
Predicted 2_DAY_RETURN: -0.0203150912106136
Predicted 7_DAY_RETURN: 27266856.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @intel: Thanks @WITHIN for the shout-out! See how Sansar and Intel recreated the @americanart Burning Man exhibit in #VR. https://t.co/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: "Intel" STOCK: 27/09/2018 DATE: 45.88 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.25 and the TextBlob polarity score is @intel. |
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: 0.0006538796861376 2_DAY_RETURN: 0.0224498692240626 3_DAY_RETURN: 0.028770706190061 7_DAY_RETURN: 15415535.0 | 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: -0.0039232781168264 PX_VOLUME: 21.26 VOLATILITY_10D: 20.328 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.25 TEXTBLOB_POLARITY: @intel | Predicted 1_DAY_RETURN: 0.0006538796861376
Predicted 2_DAY_RETURN: 0.0224498692240626
Predicted 7_DAY_RETURN: 15415535.0 |
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: Time travel, anyone? Take a virtual stroll through the original Google Garage in Street View—just like it was 20 years ago → ht…
" 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: "Not only #Gmail became extremely sluggish, Google Calendar also joined the club of the unusable apps. @Google, please, stop it.
" 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 -0.0625. |
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: -0.0625 | 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 @PayPal: Finding a Bob in America: easy. Finding online stores that accept PayPal: even easier. PayPal, accepted by 19 million sites. ht…
" STOCK: PayPal 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 0.43333333333333335. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: PayPal 1_DAY_RETURN: 0.0096640071918193 2_DAY_RETURN: 0.0117990785481516 3_DAY_RETURN: 0.0070794471288909 7_DAY_RETURN: 0.0180919204404989 | 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: PayPal LAST_PRICE: 88.99 PX_VOLUME: 6996564.0 VOLATILITY_10D: 18.979 VOLATILITY_30D: 22.722 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.43333333333333335 | Predicted 1_DAY_RETURN: 0.0096640071918193
Predicted 2_DAY_RETURN: 0.0117990785481516
Predicted 7_DAY_RETURN: 0.0180919204404989 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @JRoseland: @Google EVIDENCE of Google
Violating the privacy of users
https://t.co/NDu5nWLX4v
" 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 @Reuters: Senator Kamala Harris praises Christine Blasey Ford and demands FBI investigation into Kavanaugh allegations https://t.co/s3Xs…" 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 @Reuters: MORE: Kavanaugh says he is 'innocent' and that he has 'never done this' to Ford 'or to anyone' https://t.co/3ORUVZ2c8H" 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 0.5 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: 0.5 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 @_Wdavis55: They need to put Ed,Edd, n’ Eddy on Netflix 💯💯💯💯 @netflix
" STOCK: Netflix 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: Netflix 1_DAY_RETURN: -0.0074334795513645 2_DAY_RETURN: -0.0296288513566756 3_DAY_RETURN: -0.0291560505371541 7_DAY_RETURN: -0.0403194032202988 | 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: Netflix LAST_PRICE: 380.71 PX_VOLUME: 7326246.0 VOLATILITY_10D: 40.101 VOLATILITY_30D: 40.226 LSTM_POLARITY: -1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0074334795513645
Predicted 2_DAY_RETURN: -0.0296288513566756
Predicted 7_DAY_RETURN: -0.0403194032202988 |
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: ⚡️ Kavanaugh and Christine Blasey Ford at odds in dramatic hearing https://t.co/MTizMfxT7M" 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 -0.4333333333333333 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: -0.4333333333333333 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: "VTG Disney Store The Jungle Book Bagheera Black Panther Stuffed Plush 20 Cat https://t.co/ACdUuKetPe via @eBay" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Disney" STOCK: 27/09/2018 DATE: 116.04 | 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 -0.16666666666666666 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: 27/09/2018 1_DAY_RETURN: -0.0207687004481214 2_DAY_RETURN: -0.0281799379524302 3_DAY_RETURN: -0.0380903136849362 7_DAY_RETURN: 5195314.0 | 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: -0.0071527059634609 PX_VOLUME: 15.626 VOLATILITY_10D: 13.085 VOLATILITY_30D: -1.0 LSTM_POLARITY: -0.16666666666666666 TEXTBLOB_POLARITY: @eBay | Predicted 1_DAY_RETURN: -0.0207687004481214
Predicted 2_DAY_RETURN: -0.0281799379524302
Predicted 7_DAY_RETURN: 5195314.0 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "3D Custom Ford Mustang 5.0 License Plate/ Mustang 5.0 Blk On Black License Plate https://t.co/33rSlEtDVL via @eBay" STOCK: nan DATE: nan | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is nan and the TextBlob polarity score is nan. |
Compare the stock returns over 1, 2, 3, and 7 days after being mentioned in the tweet. Highlight any significant patterns or trends. | STOCK: nan 1_DAY_RETURN: nan 2_DAY_RETURN: nan 3_DAY_RETURN: nan 7_DAY_RETURN: nan | The stock shows a neutral return trend over the specified periods. |
Based on the given stock information, predict the 1_DAY_RETURN, 2_DAY_RETURN, and 7_DAY_RETURN. | STOCK: nan LAST_PRICE: nan PX_VOLUME: nan VOLATILITY_10D: nan VOLATILITY_30D: nan LSTM_POLARITY: nan TEXTBLOB_POLARITY: nan | Predicted 1_DAY_RETURN: nan
Predicted 2_DAY_RETURN: nan
Predicted 7_DAY_RETURN: nan |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "Ford" STOCK: 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 -0.16666666666666666 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: 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: -0.16666666666666666 TEXTBLOB_POLARITY: @eBay | 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 @KanchanGupta: Dear Nakul, I trust you don't use a smartphone, Google, or any of the apps, especially free ones. By the way @amazon is i…
" 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 0.8. |
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: 0.8 | 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 @Sony: 🚨🚨🚨 Let's roll. #SWAT Season 2 premieres tonight at 10/9c only on CBS. 🚨🚨🚨 https://t.co/rAiFbvzqX3" 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: "CBS" STOCK: 27/09/2018 DATE: 56.55 | 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 @Sony. |
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: 0.0 2_DAY_RETURN: 0.0005305039787798 3_DAY_RETURN: 0.0026525198938993 7_DAY_RETURN: 2364489.0 | 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: -0.0008841732979663 PX_VOLUME: 10.928 VOLATILITY_10D: 18.07 VOLATILITY_30D: 1.0 LSTM_POLARITY: 0.0 TEXTBLOB_POLARITY: @Sony | Predicted 1_DAY_RETURN: 0.0
Predicted 2_DAY_RETURN: 0.0005305039787798
Predicted 7_DAY_RETURN: 2364489.0 |
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: LOFTER Yoga Trapeze, Sturdy Nylon Aerial Yo... by LOFTER for $45.99 https://t.co/HLEvR8L4PR via @amazon
" STOCK: Amazon 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: Amazon 1_DAY_RETURN: -0.0189420659917138 2_DAY_RETURN: -0.0190910987689892 3_DAY_RETURN: -0.0390565231646614 7_DAY_RETURN: -0.0341185704776004 | 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: Amazon LAST_PRICE: 2012.98 PX_VOLUME: 4329391.0 VOLATILITY_10D: 28.695 VOLATILITY_30D: 22.88300000000001 LSTM_POLARITY: 1 TEXTBLOB_POLARITY: 0.0 | Predicted 1_DAY_RETURN: -0.0189420659917138
Predicted 2_DAY_RETURN: -0.0190910987689892
Predicted 7_DAY_RETURN: -0.0341185704776004 |
Analyze the sentiment expressed in the tweet. Is it positive, negative, or neutral? Explain the sentiment in relation to the stock mentioned. | TWEET: "RT @IBM: What happens when you apply technology in new ways? Plastic Bank is using IBM Blockchain to turn trash into digital credits to hel…" 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: "IBM" STOCK: 27/09/2018 DATE: 151.5 | Sentiment: (Provide sentiment here)
Explanation: The tweet sentiment is related to the stock mentioned, and it's important to interpret the context. The LSTM polarity score is 0.13636363636363635 and the TextBlob polarity score is @IBM. |
Subsets and Splits