Difference between revisions of "Project 2nd draft Derry Reyyan"
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'''Understanding change''' | '''Understanding change''' | ||
| − | Given an entity of interest, we would like to model and analyze its change | + | Given an entity of interest, we would like to model and analyze its change in terms of words and phrases that co-occur with it over time. |
We propose to construct a social graph, but instead of people, we put words as nodes and edges are weighted based on number of co-occurrence between the words. Using this social graph of words, we propose to analyze: | We propose to construct a social graph, but instead of people, we put words as nodes and edges are weighted based on number of co-occurrence between the words. Using this social graph of words, we propose to analyze: | ||
| − | + | (1) how co-occurrence with other words change over time | |
| + | (2) how the change influences the state (semantic or sentiment) associated with the entity | ||
| + | (3) how the change may correspond to events that occur during the same period of time | ||
| + | |||
| + | For example, the entity 'BP' frequently co-occurred with negatively associated words during and after the Gulf-spill event. | ||
== Dataset == | == Dataset == | ||
| Line 23: | Line 27: | ||
== Motivation == | == Motivation == | ||
| − | How does the semantic | + | How does the semantic or sentiment associated with a given entity change over time depending on its neighbor (i.e. co-occurring words/phrases)? |
| + | |||
| + | Does such change relate to a particular event that happens in the same period of time? | ||
| + | |||
| + | Can we find a natural sequence of events that define a change of state (semantic or sentiment) of a particular entity? | ||
== Techniques == | == Techniques == | ||
For each of the ideas above, proposed techniques or related papers are (in order of the ideas): | For each of the ideas above, proposed techniques or related papers are (in order of the ideas): | ||
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• Regression analysis to measure tendency of a word to become negative in meaning over time, when co-occurred with negative words (Related paper: [http://www.nejm.org/doi/pdf/10.1056/NEJMsa066082 The Spread of Obesity in a Large Social Network over 32 Years] - applied to measuring the spread of negativity in a network of words). | • Regression analysis to measure tendency of a word to become negative in meaning over time, when co-occurred with negative words (Related paper: [http://www.nejm.org/doi/pdf/10.1056/NEJMsa066082 The Spread of Obesity in a Large Social Network over 32 Years] - applied to measuring the spread of negativity in a network of words). | ||
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== Evaluation == | == Evaluation == | ||
| − | A combination of manual evaluation and cross validation (splitting the data into training and testing and evaluate) may be done | + | A combination of manual evaluation and cross validation (splitting the data into training and testing and evaluate) may be done. |
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Revision as of 18:02, 14 February 2011
Social Media Analysis Project Ideas
Team Members
Derry Wijaya [dwijaya@cs.cmu.edu]
Reyyan Yeniterzi [reyyan@cs.cmu.edu]
Project Idea
Understanding change
Given an entity of interest, we would like to model and analyze its change in terms of words and phrases that co-occur with it over time.
We propose to construct a social graph, but instead of people, we put words as nodes and edges are weighted based on number of co-occurrence between the words. Using this social graph of words, we propose to analyze:
(1) how co-occurrence with other words change over time (2) how the change influences the state (semantic or sentiment) associated with the entity (3) how the change may correspond to events that occur during the same period of time
For example, the entity 'BP' frequently co-occurred with negatively associated words during and after the Gulf-spill event.
Dataset
Motivation
How does the semantic or sentiment associated with a given entity change over time depending on its neighbor (i.e. co-occurring words/phrases)?
Does such change relate to a particular event that happens in the same period of time?
Can we find a natural sequence of events that define a change of state (semantic or sentiment) of a particular entity?
Techniques
For each of the ideas above, proposed techniques or related papers are (in order of the ideas):
• Regression analysis to measure tendency of a word to become negative in meaning over time, when co-occurred with negative words (Related paper: The Spread of Obesity in a Large Social Network over 32 Years - applied to measuring the spread of negativity in a network of words).
Evaluation
A combination of manual evaluation and cross validation (splitting the data into training and testing and evaluate) may be done.
