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👩🏻(prompt): Could you evaluate the result generated by computational method A based on these three aspects: Main entities, main events, event linkage. Result would be provided as screen shot. Please provide precision and recall for the three criteria.
model output
GPT4o Evaluation
🤖(answer): To evaluate the results of the two figures provided, one focusing on individual keyword ranking and the other using network-based community detection to extract top communities, let's break down the evaluation into the following steps:
1. Definitions for Precision and Recall:
Precision: The proportion of relevant instances among the retrieved instances. Here, it measures how many of the identified main entities, events, and linkages are actually correct and relevant.
Recall: The proportion of relevant instances that have been retrieved over the total amount of relevant instances. Here, it measures how many of the actual main entities, events, and linkages the model successfully identified.
2. Evaluation Details
Main Entities
FreePalestine:
Entities like "nazis," "holocaust," "hamas," "civilians," "israel," "palestinians," "israeli," "military," and "state" are correctly identified, focusing on relevant aspects of the conflict. However, Topic 4 ("she, her, herself, me") seems out of context and irrelevant.
Zionism:
Entities like "islam," "muslims," "israel," "us," "jews," "jewish," "ukraine," "russia," and "terrorists" are correctly identified, focusing on relevant aspects of the conflict. However, the inclusion of "ukraine" and "russia" is less directly related to the Israel-Hamas conflict.
Conclusion on Main Entities:
The method effectively identifies key entities relevant to the narratives, with some noise (irrelevant entities) particularly in the "she, her" cluster for FreePalestine and the "ukraine, russia" cluster for Zionism.
Main Events
Expert Analysis:
FreePalestine Topics:
Topic 1: nazis, holocaust, nazi, germany, hitler (references to historical events and ideologies, not specific to current events).
Topic 2: hamas, civilians, shields, israel, palestinians (indicates conflict dynamics, including civilian casualties and military actions).
Topic 3: israel, military, israeli, israelis (focuses on military actions and identity).
Topic 4: she, her, herself, me (irrelevant to the conflict's core events).
Topic 5: palestinians, palestinian, state, arms, accept (points to the broader struggle for Palestinian statehood and armed resistance).
Zionism Topics:
Topic 1: islam, muslims, muslim, ex, exmuslims (focuses on religious identity and apostasy).
Topic 2: israel, us, defend, support, israels (indicates international alliances and defense-related events).
Topic 3: jews, jewish, jew, judaism, hate (focuses on anti-Semitism and religious identity).
Topic 4: ukraine, russia, russian, russians, ukrainians (relates to another geopolitical conflict, less relevant here).
Topic 5: terrorists, terrorists, terrorism, terror, organization (focuses on terrorism-related events and organizations).
Expert Analysis:
FreePalestine:
The topics cover key aspects of the conflict, including military actions, civilian impacts, and the historical context (though this may be less event-specific). Topic 4 is unrelated.
Zionism:
The topics address religious and national identity, international alliances, and terrorism. However, the inclusion of Ukraine-Russia is off-topic for the Israel-Hamas conflict.
Conclusion on Main Events: The method identifies some key thematic areas relevant to the conflict but is less effective in pinpointing specific, contemporary events directly related to the Israel-Hamas conflict. There is some noise from unrelated topics.
Event Linkage
FreePalestine Topics:
Topic 1: Links historical ideologies (Nazism, Holocaust) with current narratives (potentially to delegitimize opponents).
Topic 2: Links Hamas, civilians, and military actions, suggesting narratives around conflict and casualty.
Topic 3: Focuses on Israeli military identity, which may be linked to ongoing military operations.
Topic 4: Does not provide meaningful linkage (irrelevant).
Topic 5: Suggests linkages around Palestinian statehood and armed resistance.
Zionism Topics:
Topic 1: Links religious identity with apostasy (may suggest narratives around religious persecution or defense).
Topic 2: Links Israel and the U.S., emphasizing defense and support, relevant to international relations narratives.
Topic 3: Links Jewish identity with anti-Semitism, suggesting narratives around religious persecution.
Topic 4: Links Ukraine-Russia conflict, which is not relevant to the Israel-Hamas conflict.
Topic 5: Links terrorism with organizational narratives, relevant to discussions on security and defense.
Expert Analysis:
FreePalestine: Event linkages are meaningful in Topics 2, 3, and 5, which connect military and civilian dynamics with broader narratives. Topic 4 fails to contribute.
Zionism: Event linkages are mostly relevant in Topics 2, 3, and 5, focusing on international support, religious identity, and terrorism. Topic 4 is irrelevant.
Conclusion on Event Linkage: The method succeeds in identifying meaningful connections in several topics but includes irrelevant linkages, particularly in unrelated geopolitical contexts.
3. Quantitative Precision and Recall Estimation:
Main Entities:
- True Positives (TP): 8 (Relevant entities: israel, hamas, palestinian civilians, israeli civilians, jewish, muslim, idf, gaza, west bank, international actors; identified: israel, hamas, jewish, muslim, civilians, people, military, palestinians).
- False Positives (FP): 2 (irrelevant terms like "she, her").
- False Negatives (FN): n(missed entities: gaza, west bank).
- recision: 8/(8+2) = 0.80
- Recall: 8/(8+2) = 0.80
2. Main Events:
- True Positives (TP): 5 (Relevant events: October 7 attack, Israeli airstrikes, ground invasion preparations, humanitarian crisis, ceasefire calls, international aid response; identified indirectly: hamas, civilians, military, statehood, terrorism).
- False Positives (FP): 2 (irrelevant topics like "she, her").
- False Negatives (FN): 2 (missed events: October 7 attack, Israeli airstrikes).
- Precision: 5/(5+2) = 0.71
- Recall: 5/(5+2)= 0.71
3. Event Linkage:
- true Positives (TP): 6 (Relevant linkages: humanitarian crisis, security measures, historical context, resistance, diplomatic efforts, international reactions; identified: military, civilians, statehood, terrorism, support, religious identity).
- False Positives (FP): 1 (irrelevant linkages like "she, her").
- False Negatives (FN): 1 (missed linkages: international reactions).
- Precision: 6/(6+1) = 0.86
- Recall: 6/(6+1) = 0.86
Overall, the topic modeling method using BERTopic shows good performance in identifying and linking the main entities, events, and thematic connections in the collective narratives on the Israel-Hamas conflict. There is some noise from irrelevant topics, but overall, the method is effective in capturing the key aspects of the discourse.