Crypto News Aggregator Mobile App Development
A crypto news aggregator handles multiple data streams simultaneously: RSS feeds, news service APIs (CryptoCompare News, CoinGecko, Messari), Twitter/X API, and price data. The challenge: consolidate everything, deduplicate, rank by relevance, and deliver to users without delay.
Data Sources and Their Characteristics
CryptoCompare News API — the free tier provides 100k requests/month, supports filtering by categories (Bitcoin, Ethereum, DeFi, NFT) and languages. Data is structured: each article contains categories, tags, source_info.
Messari API — more analytical content with a paid tier for full access. A solid source for serious financial content.
RSS Feeds — CoinDesk, Decrypt, The Block publish RSS feeds. Server-side parsing via feedparser (Python) or a custom RSS parser.
On the mobile client, don't aggregate sources directly — too many requests and battery drain. The correct approach: server aggregates and caches; the mobile client makes a single request to its own API.
Real-Time: WebSocket vs Polling
News arrives continuously. Polling every 60 seconds is a reasonable compromise for most users. WebSocket for real-time updates — if you need second-level response (e.g., breaking news).
class NewsWebSocketClient: ObservableObject {
@Published var latestNews: [NewsItem] = []
private var webSocketTask: URLSessionWebSocketTask?
func connect() {
let url = URL(string: "wss://api.yourservice.com/news/stream")!
var request = URLRequest(url: url)
request.addValue("Bearer \(token)", forHTTPHeaderField: "Authorization")
webSocketTask = URLSession.shared.webSocketTask(with: request)
webSocketTask?.resume()
listen()
}
private func listen() {
webSocketTask?.receive { [weak self] result in
if case .success(.string(let text)) = result,
let item = try? JSONDecoder().decode(NewsItem.self, from: Data(text.utf8)) {
DispatchQueue.main.async {
self?.latestNews.insert(item, at: 0)
if self?.latestNews.count ?? 0 > 200 {
self?.latestNews.removeLast()
}
}
}
self?.listen()
}
}
}
Personalization and Filtering
Users track specific coins — BTC, ETH, SOL. Client-side filtering by tags works only if all articles are already loaded. At scale — use server-side filtering with query parameters.
AI summarization: each article gets a brief 2–3 sentence summary generated via GPT-4o mini on the server during indexing. More costly than showing the original lead, but users get the gist without opening the article. Summarization cost — ~$0.0002 per article with GPT-4o mini.
Headline sentiment analysis (Positive / Neutral / Negative) — quick market signal. Use ML Kit Sentiment on Android or NLTagger.sentimentScore on iOS, or specialized crypto sentiment models (CryptoNewsScore).
Quotes Alongside Articles
Displaying the current coin price next to an article is standard for crypto aggregators. CoinGecko's free API fetches 250+ coin prices in one request: /simple/price?ids=bitcoin,ethereum&vs_currencies=usd,rub. Cache for 30 seconds to avoid excessive calls.
// Android: correlating articles with price widgets
data class NewsWithPrice(
val news: NewsItem,
val relatedCoin: CoinPrice? // null if coin not identified
)
fun enrichNewsWithPrices(
news: List<NewsItem>,
prices: Map<String, CoinPrice>
): List<NewsWithPrice> {
return news.map { item ->
val coin = item.tags.firstOrNull { prices.containsKey(it.lowercase()) }
NewsWithPrice(news = item, relatedCoin = coin?.let { prices[it.lowercase()] })
}
}
Push Notifications for Breaking News
Breaking news alerts triggered by keywords or coins from user watchlist. Firebase Cloud Messaging with topic subscriptions: /topics/bitcoin-news, /topics/ethereum-news. Users subscribe in app settings.
Frequency: no more than 3–5 pushes daily or users will unsubscribe. Background fetch (iOS) or WorkManager (Android) for quiet feed updates.
Development Process
Identifying data sources and update frequency. Server-side aggregation with deduplication and AI summarization. Mobile client: feed, filters, detail screen. Price integration. Topic-based push notifications. Watchlist personalization. Performance testing with high article volumes.
Timeline Estimates
A basic aggregator with multiple sources and filters — 4–6 weeks. Full system with AI summarization, sentiment analysis, personalization, and push notifications — 10–16 weeks.