Enhanced Sentiment Analysis Dashboard

Key Findings

Students who ultimately don't enroll display more emotionally intense conversations with higher sentiment scores, yet paradoxically, those contacted closer to or after enrollment deadlines show the highest enrollment rates, suggesting that emotional engagement and timing urgency may work through different pathways to influence enrollment decisions.

Avg Positive Sentiment

0.181

Avg Negative Sentiment

0.024

Total Transitions

569,158

Enrollment Rate

38.2%

Sentiment Transitions Overview

Direct Sentiment Shifts

14,250

Positive → Negative

12,899

Negative → Positive

Transitions through Neutral

99,066

Positive → Neutral

5,529

Negative → Neutral

5,238

Neutral → Negative

96,051

Neutral → Positive

Sentiment by Enrollment Analysis

Average Sentiment by Enrollment Status - Data

enrolled	avg_positive_sentiment	avg_negative_sentiment	student_count
0	0.194532	0.026946	11691
1	0.167682	0.020541	7225

Not enrolled students have higher average sentiment scores (both positive and negative) than enrolled students.

Sentiment Distribution Summary (Binned)

Sentiment Score Bin	Enroll Status	Freq	Sentiment
0.00-0.02	Not Enrolled	7987	neg
0.00-0.02	Enrolled	5385	neg
0.02-0.03	Not Enrolled	626	neg
0.02-0.03	Enrolled	621	neg
0.03-0.05	Not Enrolled	1239	neg
0.03-0.05	Enrolled	661	neg
0.05-0.06	Not Enrolled	367	neg
0.05-0.06	Enrolled	159	neg
0.06-0.08	Not Enrolled	569	neg
0.06-0.08	Enrolled	190	neg
0.08-0.09	Not Enrolled	218	neg
0.08-0.09	Enrolled	50	neg
0.09-0.11	Not Enrolled	266	neg
0.09-0.11	Enrolled	66	neg
0.11-0.13	Not Enrolled	146	neg
0.11-0.13	Enrolled	30	neg
0.13-0.14	Not Enrolled	72	neg
0.13-0.14	Enrolled	15	neg
0.14-0.16	Not Enrolled	57	neg
0.14-0.16	Enrolled	18	neg
0.16-0.17	Not Enrolled	37	neg
0.16-0.17	Enrolled	12	neg
0.17-0.19	Not Enrolled	32	neg
0.17-0.19	Enrolled	6	neg
0.19-0.21	Not Enrolled	45	neg
0.19-0.21	Enrolled	6	neg
0.21-0.22	Not Enrolled	8	neg
0.21-0.22	Enrolled	1	neg
0.22-0.24	Not Enrolled	6	neg
0.22-0.24	Enrolled	3	neg
0.24-0.25	Not Enrolled	2	neg
0.25-0.27	Not Enrolled	3	neg
0.25-0.27	Enrolled	1	neg
0.27-0.28	Not Enrolled	1	neg
0.28-0.30	Not Enrolled	5	neg
0.28-0.30	Enrolled	1	neg
Other	Not Enrolled	5	neg
0.00-0.03	Not Enrolled	2	pos
0.00-0.03	Enrolled	1	pos
0.03-0.05	Not Enrolled	11	pos
0.03-0.05	Enrolled	5	pos
0.05-0.08	Not Enrolled	115	pos
0.05-0.08	Enrolled	54	pos
0.08-0.11	Not Enrolled	407	pos
0.08-0.11	Enrolled	349	pos
0.11-0.13	Not Enrolled	810	pos
0.11-0.13	Enrolled	1017	pos
0.13-0.16	Not Enrolled	2511	pos
0.13-0.16	Enrolled	2717	pos
0.16-0.18	Not Enrolled	2197	pos
0.16-0.18	Enrolled	1331	pos
0.18-0.21	Not Enrolled	2091	pos
0.18-0.21	Enrolled	906	pos
0.21-0.24	Not Enrolled	1574	pos
0.21-0.24	Enrolled	424	pos
0.24-0.26	Not Enrolled	644	pos
0.24-0.26	Enrolled	137	pos
0.26-0.29	Not Enrolled	582	pos
0.26-0.29	Enrolled	125	pos
0.29-0.32	Not Enrolled	316	pos
0.29-0.32	Enrolled	65	pos
0.32-0.34	Not Enrolled	192	pos
0.32-0.34	Enrolled	35	pos
0.34-0.37	Not Enrolled	130	pos
0.34-0.37	Enrolled	19	pos
0.37-0.39	Not Enrolled	38	pos
0.37-0.39	Enrolled	10	pos
0.39-0.42	Not Enrolled	28	pos
0.39-0.42	Enrolled	13	pos
0.42-0.45	Not Enrolled	26	pos
0.42-0.45	Enrolled	8	pos
0.45-0.47	Not Enrolled	3	pos
0.45-0.47	Enrolled	1	pos
0.47-0.50	Not Enrolled	11	pos
0.47-0.50	Enrolled	5	pos
Other	Not Enrolled	3	pos
Other	Enrolled	3	pos

The sentiment distribution shows that negative sentiment is concentrated at very low scores (near 0), while positive sentiment is more spread out across higher score ranges (0.1-0.3), with both enrollment groups following similar distribution patterns.

Sentiment Flow Analysis

Sentiment Transition Matrix - Data

from_sentiment	to_sentiment	transition_count
Negative	Negative	3599
Negative	Neutral	5529
Negative	Positive	12899
Neutral	Negative	5238
Neutral	Neutral	55820
Neutral	Positive	96051
Positive	Negative	14250
Positive	Neutral	99066
Positive	Positive	276706

It's tracking the entire conversation flow (thread-level), showing how sentiment changes as the conversation progresses between AI and human messages. This gives the most comprehensive view of sentiment dynamics in the conversational.

Contact Timing vs Enrollment Rate - Data

contact_timing	total_students	enrolled_students	enrollment_rate
Early	13271	4439	33.45
Mid	3186	1531	48.05
Late	569	275	48.33
After/Very Late	1890	980	51.85

Enrollment rate increases with later contact timing, rising from 33.45% for early contact to 51.85% for after/very late contact.

Speaker-Specific Sentiment Transitions

Human Sentiment Transitions - Data

from_sentiment	to_sentiment	transition_count
Negative	Negative	703
Negative	Neutral	1931
Negative	Positive	1143
Neutral	Negative	2854
Neutral	Neutral	24290
Neutral	Positive	10769
Positive	Negative	1206
Positive	Neutral	13332
Positive	Positive	10121

Shows how human sentiment flows from one student message to the next student message, ignoring AI responses in between. This reveals whether students maintain consistent emotional states throughout their side of the conversation or if their sentiment shifts significantly as they continue engaging.

AI Sentiment Transitions - Data

from_sentiment	to_sentiment	transition_count
Negative	Neutral	1
Neutral	Negative	1
Neutral	Neutral	81587
Neutral	Positive	107050
Positive	Neutral	111364
Positive	Positive	183898

Shows how AI sentiment flows from one AI message to the next AI message, ignoring human responses in between. This reveals the emotional consistency of the AI system and whether it maintains appropriate sentiment patterns throughout its responses to student conversations.

Raw Data

Thread Sentiment Metrics

CSV

Showing all 1 rows

avg_messages_per_thread	overall_avg_positive	overall_avg_negative	highest_positive_intensity	highest_negative_intensity	avg_pos_to_neg_flips	avg_neg_to_pos_flips	total_threads
31.088708	0.184276	0.0245	1.0	1.0	0.753331	0.681909	18916

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The data shows an average of 31.09 messages per thread, with overall positive sentiment (0.184) higher than negative sentiment (0.025), and sentiment flips occurring in both directions at similar rates (0.753 positive-to-negative, 0.681 negative-to-positive) across 18,916 total threads.

Contact Timing Statistics

CSV

Showing all 1 rows

mean_days_before_deadline	min_days_before_deadline	max_days_before_deadline	total_students
125.6	-160.0	1868.0	18916

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The contact timing statistics show students are contacted an average of 125.6 days before their enrollment deadline, with a range from 160 days before to 1668 days after the deadline, across 18,916 total students.

Sentiment Direction Changes

CSV

Showing all 5 rows

dir_change	count
no_change	336125
change_to_neu	205884
first_msg	18916
pos_to_neg	14250
neg_to_pos	12899

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The sentiment direction changes show that most messages maintain their sentiment (241,822 no changes), followed by changes to neutral (155,709), with direct positive-to-negative shifts (11,799) slightly outnumbering negative-to-positive shifts (10,759).

Generated on 2025-06-08 10:38