Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T16:34:11.788535Z
Paper Citation Record · LEDGER
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset
As of 18 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2502.06180.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
15 of 15 outbound references displayed
- verified exact0
- verified fuzzy9
- unresolved4
- parse uncertain0
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation af91c71c-0eed-4d17-b97e-ca6bc6cbbdca · outbound
This paper cites Terrible experience with Uber driver! He was rude and refused to follow the GPS directions #Angry.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Terrible experience with Uber driver! He was rude and refused to follow the GPS directions #Angry
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:34:11.997294Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 599344a9-ddee-45bb-88fb-90d2fb7cd989 · outbound
This paper cites Just had the best ride ever with the friendliest driver! #HappyCustomer #GreatService.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Just had the best ride ever with the friendliest driver! #HappyCustomer #GreatService
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:34:11.984032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 80a48352-9927-4952-a874-c77a16703f9d · outbound
This paper cites My ride is taking an unfamiliar route, and I’m getting worried. Is this safe? #Fear.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset My ride is taking an unfamiliar route, and I’m getting worried. Is this safe? #Fear
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:34:11.969141Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation db852a38-72a5-4e22-bebb-39e9480a038f · outbound
This paper cites Computers in human behavior, 31:527–541.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Computers in human behavior, 31:527–541
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:34:12.024224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5023a9e4-c5e3-4f66-9d6a-37d225f2f215 · outbound
This paper cites Wow, my driver gave me a free upgrade to a luxury car! #Surprised #Love.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Wow, my driver gave me a free upgrade to a luxury car! #Surprised #Love
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:34:11.944017Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4be89c26-70f9-4337-85e9-b61886106be6 · outbound
This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:34:11.748357Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f99aca2-aabe-47fc-a1ff-ed398b3c09bf · outbound
This paper cites Use this label sparingly and only when other emotions are not evident.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Use this label sparingly and only when other emotions are not evident
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:34:11.917938Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8f7de1bd-1cc0-49d1-90c8-034e2514c0ac · outbound
This paper cites Example: "Wow, my driver gave me a free upgrade to a luxury car! #Surprised.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Example: "Wow, my driver gave me a free upgrade to a luxury car! #Surprised
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:34:11.956482Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 66b5c513-158c-4798-b42e-102c64a989fe · outbound
This paper cites Been waiting for my ride for ages. This is so frustrating!#Frustrated #LateAgain.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Been waiting for my ride for ages. This is so frustrating!#Frustrated #LateAgain
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:34:11.930942Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 90041777-c0dd-4434-bac8-716539c80cf6 · outbound
This paper cites Prompting Towards Alleviating Code-Switched Data Scarcity in Under-Resourced Languages with GPT as a Pivot.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Prompting Towards Alleviating Code-Switched Data Scarcity in Under-Resourced Languages with GPT as a Pivot
Reference 136
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-08T16:34:11.828576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e51846b4-25ab-4676-bb45-f0689204583d · outbound
This paper cites Thumbs up? Sentiment Classification using Machine Learning Techniques.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Thumbs up? Sentiment Classification using Machine Learning Techniques
Reference 2002
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:34:11.743485Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 435d1710-fb9d-4d97-9685-1c2218290649 · outbound
This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Reference 2003
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:34:11.730258Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31d08e57-c207-45b3-9837-9a481a4f964e · outbound
This paper cites Word Affect Intensities.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Word Affect Intensities
Reference 2014
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:34:11.734546Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b0b56b09-674f-41b3-ae28-2bf10e32c5b5 · outbound
This paper cites Expert Sys- tems with Applications, 209:118187.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Expert Sys- tems with Applications, 209:118187
Reference 2022
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T16:34:12.010679Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b0b7c896-a2bf-4751-ae97-0d58756b79d3 · outbound
This paper cites Sentiment Analysis Across Multiple African Languages: A Current Benchmark.
RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Sentiment Analysis Across Multiple African Languages: A Current Benchmark
Reference 2023
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-08T16:34:11.903203Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
No inbound Pith citation observations are available.