Research any topic before you write.
Find related topics. | Discover entities. | See connections. | Build a topical map.
Quantified self is both the cultural phenomenon of self-tracking with technology and a community of users and makers of self-tracking tools who share an interest in "self-knowledge through numbers". Quantified self practices overlap with the practice of lifelogging and other trends that incorporate technology and data acquisition into daily life, often…
The analysis highlights History, Applications, Technology and Measurement as prominent areas in the source structure around Quantified self.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around Quantified self shows recurring relationship patterns in the source. For example, Quantified self → An, Datum, Generally, Survey Consortium Health, The, The European Health Literacy, While Another extracted example is Quantified self → Another, Because, Data, Proponents, Rather, This. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
data quantified self health self-tracking using literacy personal technology also movement practice daily baby criticism wearable use often healthcare tracking
TTTA extracted 42 structured relationships around Quantified self. Examples in this analysis include the Fitbit or the Apple Watch → instance of → The widespread adoption in recent years of wearable fitness and sleep trackers and eating → instance of → correlate blood-sugar levels with activities. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| the Fitbit or the Apple Watch | instance of | The widespread adoption in recent years of wearable fitness and sleep trackers | 0.80 | text |
| combined with the increased presence of Internet of things in healthcare | instance of | The widespread adoption in recent years of wearable fitness and sleep trackers | 0.80 | text |
| in exercise equipment | instance of | The widespread adoption in recent years of wearable fitness and sleep trackers | 0.80 | text |
| have made self-tracking accessible to a large segment of the population.Other terms for using self-tracking data to improve daily functioning are auto-analytics | instance of | The widespread adoption in recent years of wearable fitness and sleep trackers | 0.80 | text |
| body hacking | instance of | The widespread adoption in recent years of wearable fitness and sleep trackers | 0.80 | text |
| self-quantifying | instance of | The widespread adoption in recent years of wearable fitness and sleep trackers | 0.80 | text |
| self-surveillance | instance of | The widespread adoption in recent years of wearable fitness and sleep trackers | 0.80 | text |
| sousveillance | instance of | The widespread adoption in recent years of wearable fitness and sleep trackers | 0.80 | text |
| eating | instance of | correlate blood-sugar levels with activities | 0.80 | text |
| by capturing a food record of intake | instance of | correlate blood-sugar levels with activities | 0.80 | text |
| blood glucose monitors but also Do-It-Yourself tools such as | instance of | including the use of medical devices | 0.80 | text |
| Quantified self | has application | In | 0.60 | section |
The concept neighborhoods around Quantified self bring nearby vocabulary together. In this analysis, examples include Self, Movement and Baby. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Quantified self, one of the stronger structural bridges in this analysis connects Quantified self with Applications. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Quantified self to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Applications, Technology & Measurement, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Quantified self · EN edition · Analysis: TopicsToTalkAbout