Automated emotional clustering of social media conversations

A social media intelligence platform comprising:

• a. a processor providing an analyst application comprising:
• i. a first software module obtaining real-time social media conversations;
• ii. a second software module automatically classifying, categorizing and summarizing expressed emotions in said real-time social media conversations by using a knowledge base of emotional words, or phrases, or both words and phrases as an input, wherein the knowledge base comprises a list of emotional tokens and pairwise token distance using a degree of similarity, each pair associated with a valence and arousal score expressed on a scale;
• iii. a third software module defining a continuous distance metric between said real-time social media conversations comprising same or different number of the emotional tokens utilizing an expand-align-compare (EAC) algorithm;
• and
• iv. a fourth software module conducting clustering based on that distance metric;
• b. the processor further providing a customer dashboard application comprising:
• i. a fifth software module providing an interface allowing the customer to input a topic;
• and
• ii. a sixth software module providing a graphic visualization of the sentiment clusters for the topic.

A computer-implemented social media intelligence system comprising:

• a. a digital processor performing a computer program comprising executable instructions stored on a memory device;
• b. the computer program providing a social media intelligence application comprising:
• i. a first software module obtaining real-time social media conversations;
• ii. a second software module automatically classifying, categorizing and summarizing expressed emotions in said real-time social media conversations by using a knowledge base of emotional words, or phrases, or both words and phrases as an input, wherein the knowledge base comprises a list of emotional tokens and pairwise token distance using a degree of similarity, each pair associated with a valence and arousal score expressed on a scale;
• iii. a third software module defining a continuous distance metric between said real-time social media conversations comprising same or different number of the emotional tokens utilizing an expand-align-compare (EAC) algorithm;
• iv. a fourth software module conducting hierarchical clustering based on that distance metric;
• and
• vi. a fifth software module outputting a result associated with said hierarchical clustering.

Non-transitory computer-readable storage media encoded with a computer program including instructions executable by a processor to provide a social media intelligence application comprising:

• a. a first software module obtaining real-time social media conversations;
• b. a second software module automatically classifying, categorizing and summarizing expressed emotions in said real-time social media conversations by using a knowledge base of emotional words, or phrases, or both words and phrases as an input, wherein the knowledge base comprises a list of emotional tokens and pairwise token distance using a degree of similarity, each pair associated with a valence and arousal score expressed on a scale;
• c. a third software module defining a continuous distance metric between said real-time social media conversations comprising same or different number of the emotional tokens utilizing an expand-align-compare (EAC) algorithm;
• d. a fourth software module conducting hierarchical clustering based on that distance metric;
• and
• e. a fifth software module outputting a result associated with said hierarchical clustering.